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A crucial question facing cognitive science concerns the nature of conceptual representations as well as the constraints on the interactions between them. One specific question we address in this paper is what makes cross-representational interplay possible? We offer two distinct theoretical scenarios: according to the first scenario, co-activated knowledge representations interact with the help of an interface established between them via congruent activation in a mediating third-party general cognitive mechanism, e.g., attention. According to the second scenario, co-activated knowledge representations interact due to an overlap between their features, for example when they share a magnitude component. First, we make a case for cross representational interplay based on grounded and situated theories of cognition. Second, we discuss interface-based interactions between distinct (i.e., non-overlapping) knowledge representations. Third, we discuss how co-activated representations may share their architecture via partial overlap. Finally, we outline constraints regarding the flexibility of these proposed mechanisms.
Volatile supply and sales markets, coupled with increasing product individualization and complex production processes, present significant challenges for manufacturing companies. These must navigate and adapt to ever-shifting external and internal factors while ensuring robustness against process variabilities and unforeseen events. This has a pronounced impact on production control, which serves as the operational intersection between production planning and the shop- floor resources, and necessitates the capability to manage intricate process interdependencies effectively. Considering the increasing dynamics and product diversification, alongside the need to maintain constant production performances, the implementation of innovative control strategies becomes crucial.
In recent years, the integration of Industry 4.0 technologies and machine learning methods has gained prominence in addressing emerging challenges in production applications. Within this context, this cumulative thesis analyzes deep learning based production systems based on five publications. Particular attention is paid to the applications of deep reinforcement learning, aiming to explore its potential in dynamic control contexts. Analysis reveal that deep reinforcement learning excels in various applications, especially in dynamic production control tasks. Its efficacy can be attributed to its interactive learning and real-time operational model. However, despite its evident utility, there are notable structural, organizational, and algorithmic gaps in the prevailing research. A predominant portion of deep reinforcement learning based approaches is limited to specific job shop scenarios and often overlooks the potential synergies in combined resources. Furthermore, it highlights the rare implementation of multi-agent systems and semi-heterarchical systems in practical settings. A notable gap remains in the integration of deep reinforcement learning into a hyper-heuristic.
To bridge these research gaps, this thesis introduces a deep reinforcement learning based hyper- heuristic for the control of modular production systems, developed in accordance with the design science research methodology. Implemented within a semi-heterarchical multi-agent framework, this approach achieves a threefold reduction in control and optimisation complexity while ensuring high scalability, adaptability, and robustness of the system. In comparative benchmarks, this control methodology outperforms rule-based heuristics, reducing throughput times and tardiness, and effectively incorporates customer and order-centric metrics. The control artifact facilitates a rapid scenario generation, motivating for further research efforts and bridging the gap to real-world applications. The overarching goal is to foster a synergy between theoretical insights and practical solutions, thereby enriching scientific discourse and addressing current industrial challenges.
Situated in an active tectonic region, Santiago de Chile, the country´s capital with more than six million inhabitants, faces tremendous earthquake hazard. Macroseismic data for the 1985 Valparaiso and the 2010 Maule events show large variations in the distribution of damage to buildings within short distances indicating strong influence of local sediments and the shape of the sediment-bedrock interface on ground motion. Therefore, a temporary seismic network was installed in the urban area for recording earthquake activity, and a study was carried out aiming to estimate site amplification derived from earthquake data and ambient noise. The analysis of earthquake data shows significant dependence on the local geological structure with regards to amplitude and duration. Moreover, the analysis of noise spectral ratios shows that they can provide a lower bound in amplitude for site amplification and, since no variability in terms of time and amplitude is observed, that it is possible to map the fundamental resonance frequency of the soil for a 26 km x 12 km area in the northern part of the Santiago de Chile basin. By inverting the noise spectral rations, local shear wave velocity profiles could be derived under the constraint of the thickness of the sedimentary cover which had previously been determined by gravimetric measurements. The resulting 3D model was derived by interpolation between the single shear wave velocity profiles and shows locally good agreement with the few existing velocity profile data, but allows the entire area, as well as deeper parts of the basin, to be represented in greater detail. The wealth of available data allowed further to check if any correlation between the shear wave velocity in the uppermost 30 m (vs30) and the slope of topography, a new technique recently proposed by Wald and Allen (2007), exists on a local scale. While one lithology might provide a greater scatter in the velocity values for the investigated area, almost no correlation between topographic gradient and calculated vs30 exists, whereas a better link is found between vs30 and the local geology. When comparing the vs30 distribution with the MSK intensities for the 1985 Valparaiso event it becomes clear that high intensities are found where the expected vs30 values are low and over a thick sedimentary cover. Although this evidence cannot be generalized for all possible earthquakes, it indicates the influence of site effects modifying the ground motion when earthquakes occur well outside of the Santiago basin. Using the attained knowledge on the basin characteristics, simulations of strong ground motion within the Santiago Metropolitan area were carried out by means of the spectral element technique. The simulation of a regional event, which has also been recorded by a dense network installed in the city of Santiago for recording aftershock activity following the 27 February 2010 Maule earthquake, shows that the model is capable to realistically calculate ground motion in terms of amplitude, duration, and frequency and, moreover, that the surface topography and the shape of the sediment bedrock interface strongly modify ground motion in the Santiago basin. An examination on the dependency of ground motion on the hypocenter location for a hypothetical event occurring along the active San Ramón fault, which is crossing the eastern outskirts of the city, shows that the unfavorable interaction between fault rupture, radiation mechanism, and complex geological conditions in the near-field may give rise to large values of peak ground velocity and therefore considerably increase the level of seismic risk for Santiago de Chile.
Pattern-process analysis is one of the main threads in landscape ecological research. It aims at understanding the complex relationships between ecological processes and landscape patterns, identifying the underlying mechanisms and deriving valid predictions for scenarios of landscape change and its consequences. Today, various studies cope with these tasks through so called "landscape modelling" approaches. They integrate different aspects of heterogeneous and dynamic landscapes and model different driving forces, often using both statistical and process-oriented techniques. We identify two main approaches to deal with the analysis of pattern-process interactions: the first starts with pattern detection, pattern description and pattern analysis, the second with process description, simulation and pattern generation. Focussing on the interplay between these two approaches, landscape analysis and landscape modelling will improve our understanding of pattern-process interactions. The comparison of simulated and observed pattern is a prerequisite for both approaches. Therefore, we identify a set of quantitative, robust, and reproducible methods for the analysis of spatiotemporal patterns that is a starting point for a standard toolbox for ecologists as major future challenge and suggest necessary further methodological developments. (c) 2006 Elsevier B.V. All rights reserved.
This study presents the development of 1D and 2D Surface Evolution Codes (SECs) and their coupling to any lithospheric-scale (thermo-)mechanical code with a quadrilateral structured surface mesh.
Both SECs involve diffusion as approach for hillslope processes and the stream power law to reflect riverbed incision. The 1D SEC settles sediment that was produced by fluvial incision in the appropriate minimum, while the supply-limited 2D SEC DANSER uses a fast filling algorithm to model sedimantation. It is based on a cellular automaton. A slope-dependent factor in the sediment flux extends the diffusion equation to nonlinear diffusion. The discharge accumulation is achieved with the D8-algorithm and an improved drainage accumulation routine. Lateral incision enhances the incision's modelling. Following empirical laws, it incises channels of several cells width.
The coupling method enables different temporal and spatial resolutions of the SEC and the thermo-mechanical code. It transfers vertical as well as horizontal displacements to the surface model. A weighted smoothing of the 3D surface displacements is implemented. The smoothed displacement vectors transmit the deformation by bilinear interpolation to the surface model. These interpolation methods ensure mass conservation in both directions and prevent the two surfaces from drifting apart.
The presented applications refer to the evolution of the Pamir orogen. A calibration of DANSER's parameters with geomorphological data and a DEM as initial topography highlights the advantage of lateral incision. Preserving the channel width and reflecting incision peaks in narrow channels, this closes the huge gap between current orogen-scale incision models and observed topographies.
River capturing models in a system of fault-bounded block rotations reaffirm the importance of the lateral incision routine for capturing events with channel initiation. The models show a low probability of river capturings with large deflection angles. While the probability of river capturing is directly depending on the uplift rate, the erodibility inside of a dip-slip fault speeds up headward erosion along the fault: The model's capturing speed increases within a fault.
Coupling DANSER with the thermo-mechanical code SLIM 3D emphasizes the versatility of the SEC. While DANSER has minor influence on the lithospheric evolution of an indenter model, the brittle surface deformation is strongly affected by its sedimentation, widening a basin in between two forming orogens and also the southern part of the southern orogen to south, east and west.
Predicting Paris: Multi-Method Approaches to Forecast the Outcomes of Global Climate Negotiations
(2016)
We examine the negotiations held under the auspices of the United Nations Framework Convention of Climate Change in Paris, December 2015. Prior to these negotiations, there was considerable uncertainty about whether an agreement would be reached, particularly given that the world’s leaders failed to do so in the 2009 negotiations held in Copenhagen. Amid this uncertainty, we applied three different methods to predict the outcomes: an expert survey and two negotiation simulation models, namely the Exchange Model and the Predictioneer’s Game. After the event, these predictions were assessed against the coded texts that were agreed in Paris. The evidence suggests that combining experts’ predictions to reach a collective expert prediction makes for significantly more accurate predictions than individual experts’ predictions. The differences in the performance between the two different negotiation simulation models were not statistically significant.
A polymer is a large molecule made up of many elementary chemical units, joined together by covalent bonds (for example, polyethylene). Polyelectrolytes (PELs) are polymer chains containing a certain amount of ionizable monomers. With their specific properties PELs acquire big importance in molecular and cell biology as well as in technology. Compared to neutral polymers the theory of PELs is less understood. In particular, this is valid for PELs in poor solvents. A poor solvent environment causes an effective attraction between monomers. Hence, for PELs in a poor solvent, there occurs a competition between attraction and repulsion. Strong or quenched PELs are completely dissociated at any accessible pH. The position of charges along the chain is fixed by chemical synthesis. On the other hand, in weak or annealed PELs dissociation of charges depends on solution pH. For the first time the simulation results have given direct evidence that at rather poor solvents an annealed PEL indeed undergoes a first-order phase transition when the chemical potential (solution pH) reaches at a certain value. The discontinuous transition occurs between a weakly charged compact globular structure and a strongly charged stretched configuration. At not too poor solvents theory predicts that globule would become unstable with respect to the formation of pearl-necklaces. The results show that pearl-necklaces exist in annealed PELs indeed. Furthermore, as predicted by theory, the simulation results have shown that annealed PELs display a sharp transition from a highly charged stretched state to a weakly charged globule at a critical salt concentration.
Zwischen 1990 und 1994 wurden rund 1000 Liegenschaften, die in der ehemaligen DDR von der Sowjetarmee und der NVA für militärische Übungen genutzt wurden, an Bund und Länder übergeben. Die größten Truppenübungsplätze liegen in Brandenburg und sind heute teilweise in Großschutzgebiete integriert, andere Plätze werden von der Bundeswehr weiterhin aktiv genutzt. Aufgrund des militärischen Betriebs sind die Böden dieser Truppenübungsplätze oft durch Blindgänger, Munitionsreste, Treibstoff- und Schmierölreste bis hin zu chemischen Kampfstoffen belastet. Allerdings existieren auf fast allen Liegenschaften neben diesen durch Munition und militärische Übungen belasteten Bereichen auch naturschutzfachlich wertvolle Flächen; gerade in den Offenlandbereichen kann dies durchaus mit einer Belastung durch Kampfmittel einhergehen. Charakteristisch für diese offenen Flächen, zu denen u.a. Zwergstrauchheiden, Trockenrasen, wüstenähnliche Sandflächen und andere nährstoffarme baumlose Lebensräume gehören, sind Großflächigkeit, Abgeschiedenheit sowie ihre besondere Nutzung und Bewirtschaftung, d.h. die Abwesenheit von land- und forstwirtschaftlichem Betrieb sowie von Siedlungsflächen. Diese Charakteristik war die Grundlage für die Entwicklung einer speziell angepassten Flora und Fauna. Nach Beendigung des Militärbetriebs setzte dann in weiten Teilen eine großflächige Sukzession – die allmähliche Veränderung der Zusammensetzung von Pflanzen- und Tiergesellschaften – ein, die diese offenen Bereiche teilweise bereits in Wald verwandelte und somit verschwinden ließ. Dies wiederum führte zum Verlust der an diese Offenlandflächen gebundenen Tier- und Pflanzenarten. Zur Erhaltung, Gestaltung und Entwicklung dieser offenen Flächen wurden daher von einer interdisziplinären Gruppe von Naturwissenschaftlern verschiedene Methoden und Konzepte auf ihre jeweilige Wirksamkeit untersucht. So konnten schließlich die für die jeweiligen Standortbedingungen geeigneten Maßnahmen eingeleitet werden. Voraussetzung für die Einleitung der Maßnahmen sind zum einen Kenntnisse zu diesen jeweiligen Standortbedingungen, d.h. zum Ist-Zustand, sowie zur Entwicklung der Flächen, d.h. zur Dynamik. So kann eine Abschätzung über die zukünftige Flächenentwicklung getroffen werden, damit ein effizienter Maßnahmeneinsatz stattfinden kann. Geoinformationssysteme (GIS) spielen dabei eine entscheidende Rolle zur digitalen Dokumentation der Biotop- und Nutzungstypen, da sie die Möglichkeit bieten, raum- und zeitbezogene Geometrie- und Sachdaten in großen Mengen zu verarbeiten. Daher wurde ein fachspezifisches GIS für Truppenübungsplätze entwickelt und implementiert. Die Aufgaben umfassten die Konzeption der Datenbank und des Objektmodells sowie fachspezifischer Modellierungs-, Analyse- und Präsentationsfunktionen. Für die Integration von Fachdaten in die GIS-Datenbank wurde zudem ein Metadatenkatalog entwickelt, der in Form eines zusätzlichen GIS-Tools verfügbar ist. Die Basisdaten für das GIS wurden aus Fernerkundungsdaten, topographischen Karten sowie Geländekartierungen gewonnen. Als Instrument für die Abschätzung der zukünftigen Entwicklung wurde das Simulationstool AST4D entwickelt, in dem sowohl die Nutzung der (Raster-)Daten des GIS als Ausgangsdaten für die Simulationen als auch die Nutzung der Simulationsergebnisse im GIS möglich ist. Zudem können die Daten in AST4D raumbezogen visualisiert werden. Das mathematische Konstrukt für das Tool war ein so genannter Zellulärer Automat, mit dem die Flächenentwicklung unter verschiedenen Voraussetzungen simuliert werden kann. So war die Bildung verschiedener Szenarien möglich, d.h. die Simulation der Flächenentwicklung mit verschiedenen (bekannten) Eingangsparametern und den daraus resultierenden unterschiedlichen (unbekannten) Endzuständen. Vor der Durchführung einer der drei in AST4D möglichen Simulationsstufen können angepasst an das jeweilige Untersuchungsgebiet benutzerspezifische Festlegungen getroffen werden.
Diagenetic trends of synthetic reservoir sandstone properties assessed by digital rock physics
(2021)
Quantifying interactions and dependencies among geometric, hydraulic and mechanical properties of reservoir sandstones is of particular importance for the exploration and utilisation of the geological subsurface and can be assessed by synthetic sandstones comprising the microstructural complexity of natural rocks. In the present study, three highly resolved samples of the Fontainebleau, Berea and Bentheim sandstones are generated by means of a process-based approach, which combines the gravity-driven deposition of irregularly shaped grains and their diagenetic cementation by three different schemes. The resulting evolution in porosity, permeability and rock stiffness is examined and compared to the respective micro-computer tomographic (micro-CT) scans. The grain contact-preferential scheme implies a progressive clogging of small throats and consequently produces considerably less connected and stiffer samples than the two other schemes. By contrast, uniform quartz overgrowth continuously alters the pore space and leads to the lowest elastic properties. The proposed stress-dependent cementation scheme combines both approaches of contact-cement and quartz overgrowth, resulting in granulometric, hydraulic and elastic properties equivalent to those of the respective micro-CT scans, where bulk moduli slightly deviate by 0.8%, 4.9% and 2.5% for the Fontainebleau, Berea and Bentheim sandstone, respectively. The synthetic samples can be further altered to examine the impact of mineral dissolution or precipitation as well as fracturing on various petrophysical correlations, which is of particular relevance for numerous aspects of a sustainable subsurface utilisation.
Research on novel and advanced biomaterials is an indispensable step towards their applications in desirable fields such as tissue engineering, regenerative medicine, cell culture, or biotechnology. The work presented here focuses on such a promising material: polyelectrolyte multilayer (PEM) composed of hyaluronic acid (HA) and poly(L-lysine) (PLL). This gel-like polymer surface coating is able to accumulate (bio-)molecules such as proteins or drugs and release them in a controlled manner. It serves as a mimic of the extracellular matrix (ECM) in composition and intrinsic properties. These qualities make the HA/PLL multilayers a promising candidate for multiple bio-applications such as those mentioned above. The work presented aims at the development of a straightforward approach for assessment of multi-fractional diffusion in multilayers (first part) and at control of local molecular transport into or from the multilayers by laser light trigger (second part).
The mechanism of the loading and release is governed by the interaction of bioactives with the multilayer constituents and by the diffusion phenomenon overall. The diffusion of a molecule in HA/PLL multilayers shows multiple fractions of different diffusion rate. Approaches, that are able to assess the mobility of molecules in such a complex system, are limited. This shortcoming motivated the design of a novel evaluation tool presented here.
The tool employs a simulation-based approach for evaluation of the data acquired by fluorescence recovery after photobleaching (FRAP) method. In this approach, possible fluorescence recovery scenarios are primarily simulated and afterwards compared with the data acquired while optimizing parameters of a model until a sufficient match is achieved. Fluorescent latex particles of different sizes and fluorescein in an aqueous medium are utilized as test samples validating the analysis results. The diffusion of protein cytochrome c in HA/PLL multilayers is evaluated as well.
This tool significantly broadens the possibilities of analysis of spatiotemporal FRAP data, which originate from multi-fractional diffusion, while striving to be widely applicable. This tool has the potential to elucidate the mechanisms of molecular transport and empower rational engineering of the drug release systems.
The second part of the work focuses on the fabrication of such a spatiotemporarily-controlled drug release system employing the HA/PLL multilayer. This release system comprises different layers of various functionalities that together form a sandwich structure. The bottom layer, which serves as a reservoir, is formed by HA/PLL PEM deposited on a planar glass substrate. On top of the PEM, a layer of so-called hybrids is deposited. The hybrids consist of thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) -based hydrogel microparticles with surface-attached gold nanorods. The layer of hybrids is intended to serve as a gate that controls the local molecular transport through the PEM–solution-interface. The possibility of stimulating the molecular transport by near-infrared (NIR) laser irradiation is being explored.
From several tested approaches for the deposition of hybrids onto the PEM surface, the drying-based approach was identified as optimal. Experiments, that examine the functionality of the fabricated sandwich at elevated temperature, document the reversible volume phase transition of the PEM-attached hybrids while sustaining the sandwich stability. Further, the gold nanorods were shown to effectively absorb light radiation in the tissue- and cell-friendly NIR spectral region while transducing the energy of light into heat. The rapid and reversible shrinkage of the PEM-attached hybrids was thereby achieved. Finally, dextran was employed as a model transport molecule. It loads into the PEM reservoir in a few seconds with the partition constant of 2.4, while it spontaneously releases in a slower, sustained manner. The local laser irradiation of the sandwich, which contains the fluorescein isothiocyanate tagged dextran, leads to a gradual reduction of fluorescence intensity in the irradiated region.
The release system fabricated employs renowned photoresponsivity of the hybrids in an innovative setting. The results of the research are a step towards a spatially-controlled on-demand drug release system that paves the way to spatiotemporally controlled drug release.
The approaches developed in this work have the potential to elucidate the molecular dynamics in ECM and to foster engineering of multilayers with properties tuned to mimic the ECM. The work aims at spatiotemporal control over the diffusion of bioactives and their presentation to the cells.