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Digitalization primarily takes place in and through organizations. Despite this prominent role, however, the importance of organizational structure-building processes in the digital transformation is still underexposed in discourse. The fact that ongoing digitalization is linked to an established phenomenon and its own logic, is regularly not addressed due to the attraction potential of the semantics of the digital revolution. Digital revolution and the reordering of societal relationships, though, manifest themselves primarily in processes of reorganization. Structural automation processes in the ongoing digital transformation are limiting the scope for action, necessitating forms of structural structurelessness in organizations that cultivate opportunities for chance. Since organizations realize their operations as a dual of structure and individual, and the principle of organization is therefore based on the complementarity of structural formality and unpredictable informality. The paper discusses the topicality of the classical form of modern organization in the digital age and reflects on approaches to a contemporary design of spaces of opportunity. The reflexive handling of future openness is the central task of management and leadership in order to enable variation and innovation in organizations.
Geographic ranges of species and their determinants are of great interest in the field of biogeography and are often studied in terms of the species" ecological niches. In this context, the range of a species is defined by the accessibility of an area, abiotic factors and biotic interactions, which affect a species" distributions with different intensities across spatial scales. Parapatry describes a distributional pattern in which the ranges of two species meet along sharp range limits with narrow contact zones. Such parapatric range limits are determined by changing abiotic conditions along sharp environmental gradients or can result from interspecific resource competition. However, it has been shown that often the interplay of abiotic conditions and species interactions determine parapatry. The geographic ranges of the land salamanders, Salamandra salamandra and S. atra, narrowly overlap in the European Alps with only few syntopic localities and to date, the cause of parapatry is unknown. The goal of this thesis was thus to identify the importance of abiotic and biotic factors for their parapatric range limits at different spatial scales. On a broad spatial scale, the role of climate for the parapatric range limits of the species was investigated within three contact zones in Switzerland. Climatic conditions at species" records were analysed and species distribution modelling techniques were used to explore the species" climatic niches and to quantify the interspecific niche overlap. Furthermore, it was tested whether the parapatric range limit coincides with a strong climatic gradient. The results revealed distinct niches for the species as well as the presence of strong climatic gradients which could explain the parapatric range limits of the species. Yet, there was a moderate interspecific niche overlap in all contact zones indicating that the species may co-occur and interact with each other in areas where they both find adequate conditions. Comparison among contact zones revealed geographic variation in the species" niches as well as in the climatic conditions at their records suggesting that the species can occur in a much wider range of conditions than they actually do. These findings imply that climate represents a main factor for the species" parapatric range limits. Yet, interspecific niche overlap and the geographic variation provide indirect evidence that interspecific interaction may also affect their spatial distribution. To test whether competition restricts the species" ranges on the habitat scale and to understand local syntopic co-occurrence of the salamanders within their contact zones, site-occupancy modelling was used. This approach allowed to find the habitat predictors that best explain the species" local distribution. While the slope of the site positively affected the occupancy probability of S. salamandra, no tested predictor explained that of S. atra. Also, there was no effect of the occurrence of one species on the occupancy probability of the other providing no evidence for competition. Should competition occur, it does not lead to spatial segregation of the species on this scale. Because biotic interactions most significantly affect the ranges of species on small spatial scales, the microhabitat conditions at locations of the species within syntopic contact zones were compared and a null model analysis was applied to determine their niche overlap. Resource selection probability function models were used to assess those attributes that affect the species" habitat selections. The results revealed species-specific microhabitat preferences related to leaf litter cover, tree number and that the species were active at different temperatures as well as times of the day. The high degree of diurnal activity of S. atra may be due to its preference of forest floor microhabitats that long remain suitable during daytime. Besides, there was a great niche overlap for shelters indicating that the species may compete for this resource. Differential habitat selection and the use of the available shelters at different times of the day may minimize species interactions and allow their local co-occurrence within contact zones. To identify whether the potential infection with the pathogenic chytrid fungus could serve as an alternative biotic explanation for the range margins of S. atra, several populations throughout its range were screened for infection. Since the occurrence of this pathogen was detected mostly at lower altitudes of the Alps, it may confine the range of S. atra to higher elevations. Because chytrid was not detected in any of the samples, the pathogen unlikely plays a role in determining its range limits. Overall, these findings underline the complexity of mechanisms that determine the range margins of parapatric species and provide an important basis for subsequent studies regarding the determinants of the parapatric distribution of the two salamander species.
Representation Learning techniques play a crucial role in a wide variety of Deep Learning applications. From Language Generation to Link Prediction on Graphs, learned numerical vector representations often build the foundation for numerous downstream tasks.
In Natural Language Processing, word embeddings are contextualized and depend on their current context. This useful property reflects how words can have different meanings based on their neighboring words.
In Knowledge Graph Embedding (KGE) approaches, static vector representations are still the dominant approach. While this is sufficient for applications where the underlying Knowledge Graph (KG) mainly stores static information, it becomes a disadvantage when dynamic entity behavior needs to be modelled.
To address this issue, KGE approaches would need to model dynamic entities by incorporating situational and sequential context into the vector representations of entities. Analogous to contextualised word embeddings, this would allow entity embeddings to change depending on their history and current situational factors.
Therefore, this thesis provides a description of how to transform static KGE approaches to contextualised dynamic approaches and how the specific characteristics of different dynamic scenarios are need to be taken into consideration.
As a starting point, we conduct empirical studies that attempt to integrate sequential and situational context into static KG embeddings and investigate the limitations of the different approaches. In a second step, the identified limitations serve as guidance for developing a framework that enables KG embeddings to become truly dynamic, taking into account both the current situation and the past interactions of an entity. The two main contributions in this step are the introduction of the temporally contextualized Knowledge Graph formalism and the corresponding RETRA framework which realizes the contextualisation of entity embeddings.
Finally, we demonstrate how situational contextualisation can be realized even in static environments, where all object entities are passive at all times.
For this, we introduce a novel task that requires the combination of multiple context modalities and their integration with a KG based view on entity behavior.
Avoiding aerial microfibre contamination of environmental samples is essential for reliable analyses when it comes to the detection of ubiquitous microplastics. Almost all laboratories have contamination problems which are largely unavoidable without investments in clean-air devices. Therefore, our study supplies an approach to assess background microfibre contamination of samples in the laboratory under particle-free air conditions. We tested aerial contamination of samples indoor, in a mobile laboratory, within a laboratory fume hood and on a clean bench with particles filtration during the examining process of a fish. The used clean bench reduced aerial microfibre contamination in our laboratory by 96.5%. This highlights the value of suitable clean-air devices for valid microplastic pollution data. Our results indicate, that pollution levels by microfibres have been overestimated and actual pollution levels may be many times lower. Accordingly, such clean-air devices are recommended for microplastic laboratory applications in future research work to significantly lower error rates.
In a first step, this paper analyses the emergence of the UN Sustainable Development Goals (SDGs) as new global development framework with regard to key actors, social learning cycles, innovation platforms, fundamental policy changes and transition dynamics towards sustainability. In a second step, it traces the convolution of social, political and environmental dimensions, social power relations and governance paradigms embedded in the drafting process and final framework of the water related SDG 6. This research concludes that the SDGs induced important paradigm and policy changes in addition to rearranging existing power relations.
This literature review was conducted to identify important wetlands in the Greater Accra Region and to illustrate dominant research trends, prevailing perspectives and corresponding research gaps. Six wetlands systems were identified as most significant lagoon systems, namely the Densu Delta, Sakumo, Muni-Pomadze, Keta, Korle and Songor Lagoons. Research foci for each of the respective wetlands were extrapolated and summarized in a category system. The frequency of different categories illustrates that natural science’s perspectives dominate, as most of Accra’s lagoons have been studied with regard to their ecological, physical and chemical properties. The development of research interest over time and focus on ecological baseline conditions are related to the designation of Ramsar Sites and orientation of national policies towards environmental protection. A research gap was identified, as studies link their findings to human activities but neglect the connection between governance variables and environmental developments. It is suggested to expand the natural science’s perspective on Accra’s wetlands to account for social and political aspects in order to develop a holistic and more sustainable management strategy.
In the context of accelerated global socio-environmental change, the Water-Energy-Food Nexus has received increasing attention within science and international politics by promoting integrated resource governance. This study explores the scientific nexus debates from a discourse analytical perspective to reveal knowledge and power relations as well as geographical settings of nexus research. We also investigate approaches to socio-nature relations that influence nexus research and subsequent political implications. Our findings suggest that the leading nexus discourse is dominated by natural scientific perspectives and a neo-Malthusian framing of environmental challenges. Accordingly, the promoted cross-sectoral nexus approach to resource governance emphasizes efficiency, security, future sustainability, and poverty reduction. Water, energy, and food are conceived as global trade goods that require close monitoring, management and control, to be achieved via quantitative assessments and technological interventions. Within the less visible discourse, social scientific perspectives engage with the social, political, and normative elements of the Water-Energy-Food Nexus. These perspectives criticize the dominant nexus representation for itsmanagerial, neoliberal, and utilitarian approach to resource governance. The managerial framing is critiqued for masking power relations and social inequalities, while alternative framings acknowledge the political nature of resource governance and socio-nature relations. The spatial dimensions of the nexus debate are also discussed. Notably, the nexus is largely shaped by western knowledge, yet applied mainly in specific regions of the Global South. In order for the nexus to achieve integrative solutions for sustainability, the debate needs to overcome its current discursive and spatial separations. To this end, we need to engage more closely with alternative nexus discourses, embrace epistemic pluralism and encourage multi-perspective debates about the socio-nature relations we actually intend to promote.
In this thesis, we investigate the quantization problem of Gaussian measures on Banach spaces by means of constructive methods. That is, for a random variable X and a natural number N, we are searching for those N elements in the underlying Banach space which give the best approximation to X in the average sense. We particularly focus on centered Gaussians on the space of continuous functions on [0,1] equipped with the supremum-norm, since in that case all known methods failed to achieve the optimal quantization rate for important Gauss-processes. In fact, by means of Spline-approximations and a scheme based on the Best-Approximations in the sense of the Kolmogorov n-width we were able to attain the optimal rate of convergence to zero for these quantization problems. Moreover, we established a new upper bound for the quantization error, which is based on a very simple criterion, the modulus of smoothness of the covariance function. Finally, we explicitly constructed those quantizers numerically.
We use a novel sea-ice lead climatology for the winters of 2002/03 to 2020/21 based on satellite observations with 1 km2 spatial resolution to identify predominant patterns in Arctic wintertime sea-ice leads. The causes for the observed spatial and temporal variabilities are investigated using ocean surface current velocities and eddy kinetic energies from an ocean model (Finite Element Sea Ice–Ice-Shelf–Ocean Model, FESOM) and winds from a regional climate model (CCLM) and ERA5 reanalysis, respectively. The presented investigation provides evidence for an influence of ocean bathymetry and associated currents on the mechanic weakening of sea ice and the accompanying occurrence of sea-ice leads with their characteristic spatial patterns. While the driving mechanisms for this observation are not yet understood in detail, the presented results can contribute to opening new hypotheses on ocean–sea-ice interactions. The individual contribution of ocean and atmosphere to regional lead dynamics is complex, and a deeper insight requires detailed mechanistic investigations in combination with considerations of coastal geometries. While the ocean influence on lead dynamics seems to act on a rather long-term scale (seasonal to interannual), the influence of wind appears to trigger sea-ice lead dynamics on shorter timescales of weeks to months and is largely controlled by individual events causing increased divergence. No significant pan-Arctic trends in wintertime leads can be observed.
Die Dissertation beschäftigt sich mit einer neuartigen Art von Branch-and-Bound Algorithmen, deren Unterschied zu klassischen Branch-and-Bound Algorithmen darin besteht, dass
das Branching durch die Addition von nicht-negativen Straftermen zur Zielfunktion erfolgt
anstatt durch das Hinzufügen weiterer Nebenbedingungen. Die Arbeit zeigt die theoretische Korrektheit des Algorithmusprinzips für verschiedene allgemeine Klassen von Problemen und evaluiert die Methode für verschiedene konkrete Problemklassen. Für diese Problemklassen, genauer Monotone und Nicht-Monotone Gemischtganzzahlige Lineare Komplementaritätsprobleme und Gemischtganzzahlige Lineare Probleme, präsentiert die Arbeit
verschiedene problemspezifische Verbesserungsmöglichkeiten und evaluiert diese numerisch.
Weiterhin vergleicht die Arbeit die neue Methode mit verschiedenen Benchmark-Methoden
mit größtenteils guten Ergebnissen und gibt einen Ausblick auf weitere Anwendungsgebiete
und zu beantwortende Forschungsfragen.