Marine Microbial Diversity and its role in Ecosystem Functioning and Environmental Change

Seas and oceans cover more than 70% of the Earth’s surface, host the majority of its biomass, and contribute significantly to all global cycles of matter and energy. All life on Earth most likely originated from microbes in the sea. In today’s marine ecosystems, following billions of years of evolution, microbes such as Bacteria, Archaea, viruses, fungi and protists (including microalgae), dominate the living biomass. Recent rapid developments in molecular ecology, metagenomics and ecological modelling illustrate that microbes represent the most important biological group on Earth in terms of phylogenetic and functional diversity. In addition, interdisciplinary research has uncovered new and unexpected roles of microbes in the biogeochemical cycling of carbon, nitrogen, silica and iron and many other (trace) elements in our seas and oceans. Marine microorganisms produce the organic matter and oxygen required to sustain life and facilitate the storage, transport, and turnover of key biological elements. Thus, microorganisms are the foundation of life and are of critical importance to the habitability and sustainability of our planet. (...)Peer reviewe

Oceanus.

v. 31, no. 2 (1988

Waiting through Furlough: A Geography of Disorientation

This thesis tells a story of waiting. More specifically the thesis investigates the lived experience of those who waited through furlough as part of the UK Government Coronavirus Job Retention Scheme, which paid workers to not work during the COVID-19 pandemic. Although the pandemic and the scheme form its backdrop, the thesis foregrounds understandings of how waiting through furlough was lived and felt. The thesis investigates the embodied feelings and detached work life relations experienced by those furloughed and how they narrated their experience. It draws on the accounts of furloughed workers shared in thirty-five in depth interviews, and extended attention to the spatial, temporal, corporeal, felt and tensive dimensions of waiting, through literatures of waiting, affect and queer phenomenology. In doing so the thesis argues that the detachment from work life and its rhythms made life disorientating for those waiting through furlough. As such, this thesis is also a story of disorientation. Disorientation is conceptualised in the thesis as having a plurality of forms and shaped the furlough’s capacity to act, feel and endure their situation. Spatial disorientation involves an orientation towards another who becomes an emotional marker for those furloughed. Temporal disorientation is the consequence of an orientation towards work time which is maintained, substituted for, slips or become hazy. Tensive disorientation describes how the suspension from work life is felt as a series of tensions. This study’s surfacing of the different dimensions of disorientations within a duration of waiting, potentially adds to understandings of embodied disorientations and (non)work life within geographies of waiting, disorientation, labour and COVID-19

Active Perception for Autonomous Systems : In a Deep Space Navigation Scenario

Autonomous systems typically pursue certain goals for an extended amount of time in a self-sustainable fashion. To this end, they are equipped with a set of sensors and actuators to perceive certain aspects of the world and thereupon manipulate it in accordance with some given goals. This kind of interaction can be thought of as a closed loop in which a perceive-reason-act process takes place. The bi-directional interface between an autonomous system and the outer world is then given by a sequence of imperfect observations of the world and corresponding controls which are as well imperfectly actuated. To be able to reason in such a setting, it is customary for an autonomous system to maintain a probabilistic state estimate. The quality of the estimate -- or its uncertainty -- is, in turn, dependent on the information acquired within the perceive-reason-act loop described above. Hence, this thesis strives to investigate the question of how to actively steer such a process in order to maximize the quality of the state estimate. The question will be approached by introducing different probabilistic state estimation schemes jointly working on a manifold-based encapsuled state representation. On top of the resultant state estimate different active perception approaches are introduced, which determine optimal actions with respect to uncertainty minimization. The informational value of the particular actions is given by the expected impact of measurements on the uncertainty. The latter can be obtained by different direct and indirect measures, which will be introduced and discussed. The active perception schemes for autonomous systems will be investigated with a focus on two specific deep space navigation scenarios deduced from a potential mining mission to the main asteroid belt. In the first scenario, active perception strategies are proposed, which foster the correctional value of the sensor information acquired within a heliocentric navigation approach. Here, the expected impact of measurements is directly estimated, thus omitting counterfactual updates of the state based on hypothetical actions. Numerical evaluations of this scenario show that active perception is beneficial, i.e., the quality of the state estimate is increased. In addition, it is shown that the more uncertain a state estimate is, the more the value of active perception increases. In the second scenario, active autonomous deep space navigation in the vicinity of asteroids is investigated. A trajectory and a map are jointly estimated by a Graph SLAM algorithm based on measurements of a 3D Flash-LiDAR. The active perception strategy seeks to trade-off the exploration of the asteroid against the localization performance. To this end, trajectories are generated as well as evaluated in a novel twofold approach specifically tailored to the scenario. Finally, the position uncertainty can be extracted from the graph structure and subsequently be used to dynamically control the trade-off between localization and exploration. In a numerical evaluation, it is shown that the localization performance of the Graph SLAM approach to navigation in the vicinity of asteroids is generally high. Furthermore, the active perception strategy is able to trade-off between localization performance and the degree of exploration of the asteroid. Finally, when the latter process is dynamically controlled, based on the current localization uncertainty, a joint improvement of localization as well as exploration performance can be achieved. In addition, this thesis comprises an excursion into active sensorimotor object recognition. A sensorimotor feature is derived from biological principles of the human perceptual system. This feature is then employed in different probabilistic classification schemes. Furthermore, it enables the implementation of an active perception strategy, which can be thought of as a feature selection process in a classification scheme. It is shown that those strategies might be driven by top-down factors, i.e., based on previously learned information, or by bottom-up factors, i.e., based on saliency detected in the currently considered data. Evaluations are conducted based on real data acquired by a camera mounted on a robotic arm as well as on datasets. It is shown that the integrated representation of perception and action fosters classification performance and that the application of an active perception strategy accelerates the classification process