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"Come together in Rostock"
(2023)
"Ein Brandenburger Weg"?
(2023)
"Il Gattopardo" nella DDR
(2023)
Sulla base di materiale d'archivio inedito si ripercorre l'avvincente storia della prima edizione del Gattopardo nella DDR (1961). È qui analizzata la corsa ad ostacoli del romanzo tra congruenze ed eccezioni che assume i tratti di un giallo letterario. L'opera di un principe defunto scavalca il Muro grazie ad Alfred Kurella, potente funzionario della SED. Nella sua postfazione Il Gattopardo non è canto della decadenza, ma preannuncio di una nuova epoca, manifesto dello Stato in procinto di entrare nell'era socialista. La chiave di lettura è un unicum con una marcata impronta ideologica che ne determina prima la fortuna e poi l'isolamento. Al Gattopardo nella Germania Est Bernardina Rago dà per la prima volta voce.
"Rock gegen Kommunismus"
(2023)
#Gesellschaftslehre 9/10
(2023)
#WAT 5/6
(2023)
Im Sinne einer „Meta-Reflexivität“ zielt dieser Beitrag darauf ab, den strukturtheoretischen und kompetenzorientierten Professionalisierungsansatz im Konstrukt der adaptiven Lehrkompetenz zusammenzuführen, was vor allem für inklusionsorientierte Ansätze vielversprechend erscheint: Anhand der Konstruktfacetten adaptiver diagnostischer, didaktischer sowie Sach- und Klassenführungskompetenz werden mögliche Herangehensweisen für eine inklusionsorientierte Lehrkräftebildung formuliert, die sowohl konkrete Kompetenzbereiche benennen als auch die Reflexion entsprechender Spannungsverhältnisse im strukturtheoretischen Sinne voraussetzen. So soll der Beitrag einen knappen theoretischen Aufriss zur Zusammenführung der unterschiedlichen Professionalisierungsansätze unter der Prämisse (mehr) Reflexion für (mehr) Inklusion leisten.
(Moralisch) guter Sex
(2023)
In einem kürzlich erschienenen Artikel argumentiert Almut v. Wedelstaedt überzeugend, warum Zustimmung zwar „die Bedingung für die Legitimation von Sex“ ist (2020, 127), dass die moralische Güte von Sex aber nur dann einzuschätzen ist, wenn wir darauf achten, ob die Beteiligten der Handlung sich auf Augenhöhe begegnen. Die Idee ist: Es gibt legitime sexuelle Handlungen, die moralisch gut sind, und es gibt legitime sexuelle Handlungen, die moralisch besser sind. Hier möchte ich die Idee des besseren Sexes genauer ausloten. Während v. Wedelstaedt von moralisch gelungenem Sex spricht und somit auf der Ebene der moralischen Bewertung von Sex bleibt, möchte ich die Frage danach stellen, was Sex qualitativ gut macht. Tatsächlich wird in der Zustimmungsdebatte meist davon ausgegangen, dass diese zwei Fragen wenig gemeinsam haben; ob eine sexuelle Handlung legitim ist, hat zunächst nichts damit zu tun, ob diese auch gut ist. Ich werde drei Argumente liefern, warum wir legitimen Sex und qualitativ guten Sex zusammen betrachten sollten – und es wird sich zeigen, dass die gegenwärtige philosophische und rechtstheoretische Debatte Zustimmung verkürzt diskutiert und daher alleingenommen wenig hilfreich ist, stattdessen benötigt die Zustimmungsdebatte auch eine Untersuchung von qualitativ gutem Sex.
1933
(2023)
The emerging threat of antibiotic-resistant bacteria has become a global challenge in the last decades, leading to a rising demand for alternative treatments for bacterial infections. One approach is to target the bacterial cell envelope, making understanding its biophysical properties crucial. Specifically, bacteriophages use the bacterial envelope as an entry point to initiate infection, and they are considered important building blocks of new antibiotic strategies against drug-resistant bacteria.. Depending on the structure of the cell wall, bacteria are classified as Gram-negative and Gram-positive. Gram-negative bacteria are equipped with a complex cell envelope composed of two lipid membranes enclosing a rigid peptidoglycan layer. The synthesis machinery of the Gram-negative cell envelope is the target of antimicrobial agents, including new physical sanitizing procedures addressing the outer membrane (OM). It is therefore very important to study the biophysical properties of the Gram-negative bacterial cell envelope. The high complexity of the Gram-negative OM sets the demand for a model system in which the contribution of individual components can be evaluated separately. In this respect, giant unilamellar vesicles (GUVs) are promising membrane systems to study membrane properties while controlling parameters such as membrane composition and surrounding medium conditions.
The aim of this work was to develop methods and approaches for the preparation and characterization of a GUV-based membrane model that mimics the OM of the Gram-negative cell envelope. A major component of the OM is the lipopolysaccharide (LPS) on the outside of the OM heterobilayer. The vesicle model was designed to contain LPS in the outer leaflet and lipids in the inner leaflet. Furthermore, the interaction of the prepared LPS-GUVs with bacteriophages was tested. LPS containing GUVs were prepared by adapting the inverted emulsion technique to meet the challenging properties of LPS, namely their high self-aggregation rate in aqueous solutions. Notably, an additional emulsification step together with the adaption of solution conditions was employed to asymmetrically incorporate LPS containing long polysaccharide chains into the artificial membranes. GUV membrane asymmetry was verified with a fluorescence quenching assay. Since the necessary precautions for handling the quenching agent sodium dithionite are often underestimated and poorly described, important parameters were tested and identified to obtain a stable and reproducible assay. In the context of varied LPS incorporation, a microscopy-based technique was introduced to determine the LPS content on individual GUVs and to directly compare vesicle properties and LPS coverage. Diffusion coefficient measurements in the obtained GUVs showed that increasing LPS concentrations in the membranes resulted in decreased diffusivity.
Employing LPS-GUVs we could demonstrate that a Salmonella bacteriophage bound with high specificity to its LPS receptor when presented at the GUV surface, and that the number of bound bacteriophages scaled with the amount of presented LPS receptor. In addition to binding, the bacteriophages were able to eject their DNA into the vesicle lumen. LPS-GUVs thus provide a starting platform for bottom-up approaches for the generation of more complex membranes, in which the effects of individual components on the membrane properties and the interaction with antimicrobial agents such as bacteriophages could be explored.
A circulatory loop
(2023)
In the digitalization debate, gender biases in digital technologies play a significant role because of their potential for social exclusion and inequality. It is therefore remarkable that organizations as drivers of digitalization and as places for social integration have been widely overlooked so far. Simultaneously, gender biases and digitalization have structurally immanent connections to organizations. Therefore, a look at the reciprocal relationship between organizations, digitalization, and gender is needed. The article provides answers to the question of whether and how organizations (re)produce, reinforce, or diminish gender‐specific inequalities during their digital transformations. On the one hand, gender inequalities emerge when organizations use post‐bureaucratic concepts through digitalization. On the other hand, gender inequalities are reproduced when organizations either program or implement digital technologies and fail to establish control structures that prevent gender biases. This article shows that digitalization can act as a catalyst for inequality‐producing mechanisms, but also has the potential to mitigate inequalities. We argue that organizations must be considered when discussing the potential of exclusion through digitalization.
Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items.
However, there are two major empirical challenges to the theory: (i) Grammatical sentences’ data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect.
The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges.
To explain the grammatical sentences’ data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption.
To account for the absence of facilitatory effect in antecedent-reflexive dependencies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III).
Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation.
The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.
National Action Plans (NAPs) have been increas-ingly adopted world-wide after the Vienna Dec-laration in 1993, where it was urged to consider the improvement and promotion of Human Rights. In this paper, we discuss their usefulness and success by analysing the challenges present-ed during NAP processes as well as the benefits this set of actions entails: The challenges for their implementation outweigh its actual benefits. Nevertheless, NAPs have great potential. Based on new research, we elaborate a set of recom-mendations for improving the design and imple-mentation of national action planning. In order to effectively bring NAP into practice, we consider it crucial to plan and analyse every state local circumstances in detail. The latter is important, since the implementation of a concrete set of actions is intended to directly transform and improve the local living conditions of the people. In a long-term perspective, we defend the benefit of NAP’s implementation for complying obliga-tions set up by HR treaties.
The last years have been affected by Covid-19 and the international emergency mecha-nism to deal with health-related threats. The effects of this period manifested differ-ently worldwide, depending on matters such as international relations, national policies, power dynamics etc. Additionally, the impact of this time will likely have long-term effects which are yet to be known. This paper gives a critical overview of the Public Health Emergency of International Concern (PHEIC) mechanism in the context of Covid-19. It does so by explaining the legal framework for states of emergency, specifically in the context of a PHEIC, while considering its restrictions and limitations on human rights. It further outlines issues in the manifestation of global protections and limitations on human rights during Covid-19. Lastly, considering the likelihood of future PHEICs and the known systemic obstructions, this paper offers ways to im-prove this mechanism from a holistic, non-zero-sum perspective.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.