6949 research outputs found
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Gudiance on research data management and data sharing of qualitative research data
No full textDie vorliegende Handreichung adressiert die besonderen Herausforderungen des Forschungsdatenma nagements (FDM) qualitativer Daten. Sie benennt zentrale Aspekte, die sowohl bei der Planung und Durchführung der Forschung als auch bei der Vorbereitung der Daten für die wissenschaftliche Nach nutzung berücksichtigt werden sollten. Ausgangspunkt sind die Besonderheiten qualitativer Forschung, die die Anwendung standardisierter und generischer FDM-Vorlagen häufig an ihre Grenzen führt.
Die Handreichung beleuchtet zentrale Schritte des FDM wie die frühzeitige Einbindung von FDZ, die Gestaltung der informierten Einwilligung, die Entwicklung datensatzspezifischer Anonymisierungskonzepte und die umfassende Kontextualisierung der Daten. Sie befürwortet ein flexibles Instrumentarium, welches den offenen, iterativen Charakter qualitativer Forschung widerspiegelt und bietet Forschenden eine strukturierte Vorgehensweise für das FDM qualitativer Daten. Ein zentrales Anliegen ist die Förde rung einer Kultur des Data Sharing, die die wissenschaftliche Nachnutzung qualitativer Forschungsdaten ermöglicht, die Rechte aller Beteiligten wahrt und forschungsethischen Anforderungen entspricht.
Die vorliegende Handreichung ist im Rahmen des Netzwerks QualidataNet (www.qualidatanet.org) entstanden, ein Netzwerk von Akteuren welches im Rahmen der Nationalen Forschungsdateninfrastruktur (NFDI) im Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften (KonsortSWD-NFDI4Society) aufgebaut wurde und betrieben wird. QualidataNet bündelt die Expertise mehrerer Forschungsdatenzentren (FDZ) und Data Provider, die spezialisierte Dienstleistungen für die Archivierung und Bereitstellung qualitativer Forschungsdaten anbieten
The Health Care System in Cuba
No full textThis country report provides a description of the emergence of a health care system under public responsibility in Cuba. The inception of the health care system refers to the first legislation stipulating entitlements to medical care. The report also includes a brief description of major health care reforms, and the current organization of the health care system in Cuba. This report is part of the CRC 1342 Social Policy Country Briefs Series.005
Integration of SiO2 aerogels in microchips and their role as catalyst supports for H₂ combustion devices
No full textSilica aerogels are porous materials with high specific surface area, open
porosity, and low thermal conductivity. These unique properties make them
promising candidates for applications such as catalyst supports and thermal
insulation. Although silica aerogels have already been incorporated in
microsystems; their high shrinkage and fragile behaviour have limited their use to
particles, thin films and droplets. This work investigates (I) a process for realising
shrinkage-free silica aerogel monoliths inside microfluidic channels and (II) their
application as catalytic supports in hydrogen combustion microdevices.
The silica aerogels were realised using a sol-gel method with a two-step
catalysis. Tetraethyl orthosilicate was used as the silica precursor. To overcome
the shrinking and improve the mechanical strength of the aerogels, CO2
supercritical drying and mechanical additives (polyethylene glycol and carbon
nanotubes) were applied. Critical process parameters observed were the filling
of the microchannels during gelation to avoid shrinkage inside the channel; one week aging time; and twenty exchange cycles during drying to completely
remove the ethanol from the pores and avoid pore collapse. The resulting
aerogels were successfully integrated in the microchannels without shrinkage.
The various compositions of aerogels exhibited high specific surface areas, in a
range of 374 to 551 m2/g and mesoporosity. The aerogels were also successfully
reinforced by polyethylene glycol and carbon nanotubes (2 to 8 wt.%). The
reinforced aerogel monoliths showed an increase of the compressive strength
up to three times higher than pure silica aerogels.
To explore catalytic applications, the aerogels were functionalized with
platinum and ruthenium nanoparticles with concentrations of 2 to 10 wt.%. For this
study, a new chip design was used, featuring a polyimide membrane-based open
cavity with platinum thermal structures, enabling both the nanoparticle
integration and in-situ reaction characterization. Nanoparticles were dispersed in
ethanol and infiltrated into the aerogel after drying, ensuring deep penetration
and uniform distribution. The catalytic system was characterised using SEM,
STEM, EXD, XRD and H2 chemisorption. Additionally, the catalytic combustion was
monitored directly in the chip by measuring the resistance change of the
thermistor. The final nanoparticle integrated aerogel system could initiate
hydrogen combustion in the chip at different loading of Platinum (2 to 10 wt%)
and gas composition (0.5 – 2 % vol H2/air). The catalytic reaction also proceeded
independently of pre-heating of the system, where a variation of 40oC was
measured.
Overall, this work establishes a scalable methodology for integrating silica
aerogels into microfluidic channels without shrinkage and demonstrates their
viability as catalytic supports for platinum nanoparticles in hydrogen combustion
devices
Thermografische Detektion von Erosionsschäden an Rotorblättern von Windenergieanlagen
No full textZiel der Arbeit ist die Nutzbarmachung der Thermografie für die in situ- sowie die in-Prozess-Analyse lokaler Schädigungen an Rotorblattvorderkanten von Windenergieanlagen. Untersucht werden Detektionsgrenzen initialer Defekte unter realitätsnahen Bedingungen, Ansätze zur Klassifizierung und Prognose von Regenerosionsschäden auf Basis thermografischer Merkmale sowie erosionsinduzierte Strömungseffekte zur Schadensanalyse im Betriebszustand. Simulation und Experiment belegen die Eignung der Langpuls-Thermografie zur zerstörungsfreien Detektion initialer Defekte, insbesondere von Lufteinschlüssen in glasfaserverstärkten Kunststoffen. An gekrümmten beschichteten Probekörpern werden Defekte bis zu einem Aspektverhältnis Γz von 2,0 in Simulationen und 1,2 in Experimenten bei CNR ≥ 4 zuverlässig nachgewiesen. Eine angepasste Wahl der Anregungsparameter und eine optimierte Bildverarbeitung steigern die Detektierbarkeit. Für die Entwicklung von Regenerosionsschäden zeigt sich, dass Beschichtung, initiale Defekte und deren Lage in den Randschichten die Zeit bis zu Oberflächenschäden maßgeblich bestimmen, wobei thermografische Messungen den Fortschritt visualisieren, quantifizieren und klassifizieren. Zur Bewertung kleiner Kavitäten an der Vorderkante wird thermografische Strömungsvisualisierung eingesetzt. Windkanalversuche und numerische Strömungssimulationen zeigen eine stromaufwärtige Verlagerung der Transition sowie charakteristische Turbulenzmuster, die von Defektposition, Profilform, Anströmgeschwindigkeit und Defektgeometrie abhängen. Damit wird eine indirekte Zustandsbewertung aus der strömungsmechanischen Reaktion ermöglicht und eine Basis für praxistaugliche Prüfverfahren, automatisierte Zustandsüberwachung und belastbare Lebensdauerprognosen geschaffen
Towards understanding of future Arctic Ocean using high-resolution FESOM2 model
No full textThe Arctic Ocean is currently experiencing some of the most rapid, complex, and far-reaching climatic transformations on Earth. These changes are driven by intensified global warming and manifest through a combination of diminishing sea ice, altered ocean circulation, and shifting atmospheric interactions. Despite the Arctic's central role in regulating planetary climate feedbacks, most global climate models still lack the spatial resolution required to adequately represent mesoscale eddies. These eddies, which are typically on the scale of a few to tens of kilometres, are critical for capturing key processes such as lateral heat transport, vertical mixing, and the redistribution of tracers and momentum. Their influence is particularly pronounced in the Arctic, where steep gradients in temperature and salinity, along with seasonal sea-ice variability, create an environment highly susceptible to small-scale dynamical features. In this study, we apply a next-generation global sea ice–ocean model configured with kilometre-scale horizontal resolution, specifically optimized for high-latitude processes, to investigate how Arctic eddy activity responds under conditions of sustained warming. Our findings show that in a world that has warmed by 4 degrees Celsius, the average eddy kinetic energy increases significantly, approximately tripling relative to present-day levels. This robust increase is primarily attributed to stronger baroclinic instability, which arises due to intensified lateral density gradients and extensive sea-ice retreat. Beyond this energetic amplification, the simulations reveal notable structural changes in eddy distribution across depth layers. While the number of eddies in mid-to-deep waters decreases, those that remain tend to become larger in size, suggesting that energy is concentrated into fewer but more vigorous features. At the same time, the upper ocean experiences a sharp rise in the number and strength of near-surface eddies, driven by increased wind forcing and surface buoyancy fluxes in newly ice-free regions. Recognizing the essential role of mesoscale eddies in Arctic circulation and vertical heat exchange, we further examine how these evolving patterns affect sea-ice seasonality. Our analysis indicates that under accelerated warming, the probability of predominantly ice-free Arctic summers becomes considerably higher. A direct comparison between eddy-rich and eddy-present model configurations demonstrates that the higher-resolution configuration, which explicitly resolves mesoscale processes, produces a significantly extended open-water season by the end of the century. This extension is closely associated with enhanced upper-ocean vertical mixing, which results from elevated shear and weakened stratification linked to the intensification of near-surface eddies. Consequently, summer sea-ice melting begins earlier, while autumn freeze-up is delayed, revealing the high sensitivity of sea-ice regimes to fine-scale ocean dynamics. Taken together, these findings highlight the intricate and interconnected mechanisms by which the Arctic climate system responds to external forcing. From the substantial increase in eddy kinetic energy and the enlargement of deep eddy structures, to the intensification of surface eddy activity and the shift in sea-ice timing, our study underscores the importance of high-resolution ocean modeling in capturing these critical dynamics. In addition to its implications for sea-ice extent, enhanced eddy-driven mixing has broader consequences for marine heatwave development, nutrient cycling, and primary productivity, thereby influencing biodiversity and ecosystem resilience. Moreover, by shedding light on the interactions between mesoscale eddies and large-scale oceanic and atmospheric circulation patterns, our results provide an essential scientific basis for improving future projections of Arctic environmental change. To fully understand and predict the impacts of these evolving processes, we recommend a coordinated research effort that combines high-resolution modeling with comprehensive observational strategies. These should include advanced satellite measurements, expanded autonomous observing platforms, and targeted field campaigns designed to resolve fine-scale variability in ocean and ice dynamics. Such integrated approaches are vital for capturing the full spectrum of mesoscale influences on the Arctic system and for assessing their implications within the broader context of Earth system change
Constraint-based causal discovery with tiered background knowledge
No full textThis thesis explores how information about temporal structures can improve causal discovery methods. I consider extensions of existing constraint-based causal discovery algorithms: The PC, FCI, and IOD. These algorithms estimate graphs based on (conditional) independence testing, and are originally purely data-driven. However, often we have more information available than only the dependence structure. This I refer to as background knowledge, and this can be used to extend and improve the existing algorithms. In this thesis, I focus on information given by a temporal order, e.g. in which order variables are measured. This entails a special kind of background knowledge, which I refer to as temporal, or tiered, background knowledge.
The fact that the use of tiered background knowledge improves causal discovery methods appears evident. The novel contribution of this thesis is a thorough investigation of the ways in which the algorithms are improved. This includes formal results and examples, as well as empirical results using both simulated and real data. The improvements due to tiered background knowledge fall into one of two categories: Informativeness and accuracy. Constraint-based causal discovery suffer from an under-identifiability of the causal structure, since multiple graphs may encode the same dependence structure. An improvement in informativeness means an increased certainty of the causal connections. In practice, the output graphs are often incorrect due to errors arising from independence testing using finite sample data. An improvement in accuracy means that the estimated graphs are less prone to errors.
This thesis presents a formalisation of (tiered) background knowledge, and results on how it improves constraint-based causal discovery in different aspects under different assumptions:
First, I assume that all relevant variables are observed, and that we are given the correct (conditional) independencies among the observed variables. I give a criterion for when an increase in informativeness is obtained by adding tiered background knowledge. This criterion suggests that adding background knowledge of early tiers yields the largest increase in informativeness, with the overall largest increase for sparse graphs. This is supported by the results of a simulation study. Moreover, I show that the graphical output has some desirable interpretational and computational properties.
Second, I relax the assumption of knowing the correct (conditional) independencies among the observed variables. However, I still assume that all relevant variables are observed. I consider the properties of the existing tiered PC (tPC) algorithm. This is an extension of the original PC, which skips some conditional independence tests and orients some (additional) edges, both based on tiered background knowledge. I show how this improves the accuracy.
Third, I again assume knowledge of (conditional) independencies among the observed variables. However, I allow for unobserved variables, and I combine multiple overlapping datasets. I describe the existing tiered FCI (tFCI) and introduce the novel tiered IOD (tIOD), which both extend the existing algorithms with tiered background knowledge, similar to the tPC. The output of the IOD algorithm consists of multiple graphs, which implies an additional level of under-identifiability. I show that tiered background knowledge can decrease this number of graphs.
Lastly, I discuss how the results presented here relate to similar work, as well as some open problems and possible extensions. All algorithms are provided as pseudo-algorithms, and are accompanied by proofs of soundness, and often also completeness
A framework for sensor fault detection and management in low-power IoT edge devices
No full textWith the rapid development of the Internet of Things (IoT), reliable and energy-efficient provision of IoT applications is of utmost importance. In this context, the effective operation of IoT applications largely depends on sensor functionality, which can be compromised by various factors such as environmental conditions, vandalism, or sensor degradation.
Ensuring the reliability and efficiency of \ac{IoT} applications requires robust, flexible, and effective tools for fault detection and management. However, achieving robustness, accuracy, and efficiency in current anomaly detection and management techniques is challenging. Faulty sensor measurements might not always manifest as obvious deviations from the norm and can resemble normal behavior. Conversely, legitimate fluctuations may be misinterpreted as anomalies. Moreover, the scarcity of labeled real-world faulty sensor data complicates the accurate evaluation of fault detection models. Additionally, the limited operational flexibility and resources of low-power edge devices introduce difficulties in timely fault management and reconfiguration. This thesis presents an advanced framework for sensor fault detection and management, to address the above challenges. The proposed fault detection solution, AssureSense, integrates a robust feature extraction method called TsAssure, which effectively identifies subtle and hidden faults in sensor data. TsAssure captures essential temporal, local, and spatial features from sensor measurements and their correlations, enhancing the understanding of sensor behavior. This capability enables AssureSense to detect anomalies with a shorter training phase, making it suitable for real-world applications. Once faults are identified, the framework also includes two strategies for remotely managing and mitigating the impact of faulty sensors. These strategies leverage the Over-the-Air (OTA) update paradigm to reconfigure the system. To evaluate the proposed methods, collections of labeled datasets were obtained from experimental situations containing both normal and faulty sensors. Testing with these datasets demonstrates that AssureSense outperforms existing methods in accurately detecting anomalies. Furthermore, experiments reveal that TsAssure surpasses other established feature extraction techniques in accurately capturing sensor behaviors and helps the fault detection techniques to more accurately detect abnormal measurements.
In parallel, this thesis also addresses the challenge of collecting real-world faulty data by proposing a novel approach to model faulty sensor measurements, which generates more realistic synthetic data that can be used to train fault detection algorithms.
Evaluating the proposed fault model in comparison with current models demonstrates that this approach more effectively represents sensor faults, leading to improved identification of real-world faulty data compared to traditional fault models
Seasonal Fluctuations and Trends: An Examination of Socioeconomic Sustainability on the Turkish Mediterranean Coast
No full textSaisonale Schwankungen stellen eine zentrale Herausforderung für die sozioökonomische Nachhaltigkeit von Tourismusdestinationen dar, da sie die physische Tragfähigkeit der Destinationen maßgeblich beeinflussen kann. Diese Masterarbeit untersucht zwei ausgewählte Reiseziele an der türkischen Mittelmeerküste hinsichtlich ihrer saisonalen Schwankungen und langfristigen Trends. Dabei werden zwei methodische Ansätze verfolgt: Erstens wird die physische Tragfähigkeit der Destinationen anhand qualitativer Daten analysiert, unterstützt durch Experteninterviews mit Vertretern aus der Hotellerie und dem deutschen Konsulat. Zweitens erfolgt eine quantitative Modellierung mit dem Datenverarbeitungsprogramm EViews, um die saisonalen Muster sowie den Einfluss geopolitischer Ereignisse auf den Tourismus zu evaluieren. Die Stärken und Schwächen beider Modelle werden diskutiert, um eine fundierte Einschätzung ihrer Aussagekraft für eine nachhaltige Tourismusentwicklung zu ermöglichen. Die gewonnenen Erkenntnisse sollen dazu beitragen, Strategien zur Reduzierung saisonaler Abhängigkeiten zu entwickeln und eine ausgewogene wirtschaftliche Entwicklung in den betroffenen Regionen zu fördern
Environmental change since the Late Pleistocene in the eastern Patagonian Andes (46.5º S): insights from geomorphology and lake sediments.
No full textUnderstanding Earth-surface processes at the margins of former ice sheets is key to reconstruct past environmental variability and anticipate landscape responses to climate change. The Meseta Chile Chico (71.6º-72.0º W, 46.5º-46.8 º S), a volcanic plateau in the eastern Patagonian Andes, offers key insights into glacial, tectonic, and climatic interactions. This study integrates landform characterizations and lacustrine sediment records from this region, to reconstruct environmental change from the Late Pleistocene throughout the Holocene.
Geomorphological evidence shows that the rugged topography of the Meseta Chile Chico developed through enhanced erosion driven by tectonic uplift and glacial isostatic rebound at least since the Late Pliocene. During the Last Glacial Maximum, its surrounding valleys were glaciated while the plateau surface was shaped by periglacial processes such as freeze-thaw cycles and nivation. After deglaciation, slope instability increased along plateau margins due to paraglacial debuttressing and regional base-level changes. Thereafter, these processes became increasingly influenced by Holocene climatic variability.
A continuous sediment record from Laguna Meseta, a lake on the plateau, reflects ca. 10,000 years of postglacial environmental change. High lake productivity persisted, since 10,000 until 5500 cal yr BP, when a marked increase in detrital input, linked to enhanced runoff, coincided with the Mid-Holocene glacier advance, documented across Patagonia.
Additional insights come from Laguna Vogt, a lake on the southwestern margin of Meseta Chile Chico, which provides a high-resolution record of the last ca. 1600 years. Its sediments show that runoff-driven detrital input remained dominant into the Late Holocene. In contrast, between 1300-1000 and 750-250 cal yr BP, runoff markedly decreased, while periods of high lake productivity alternated with flooding events. These instable conditions suggest shifts between wet-cold and dry-warm phases and marked the onset of seasonality. At ca. 250 al yr BP, allochthonous input increased again, consistent with the last glacial advance of the Holocene.
These environmental reconstructions suggest that high runoff intensities were mainly driven by precipitation. Combined with low temperatures, these conditions led to neoglacial stages associated with latitudinal shifts and expansion of the Southern Hemisphere Westerly Winds (SWW), as indicated by former regional studies. This correlation suggests that Holocene climate at the eastern margin of the Patagonian Andes was primarily controlled by the SWW, while intervals of enhanced seasonality played a key role on multi-centennial timescales.
Overall, this integrated reconstruction highlights the complex interplay among tectonic forces, glacial, periglacial and postglacial activity, and atmospheric circulation in central west Patagonia. It underscores the value of combining geomorphology and sediment proxies to understand long-term environmental change and improve predictions of how such dynamic landscapes may respond to future climate shifts
From abstract systems to concrete chips: bridging gaps in abstraction techniques for design, verification and optimization with modern system-based hardware development
No full textThe increasing complexity of System-on-Chips (SoCs) requires new methods and techniques to handle the space of architectural possibilities and the need for optimization, verification, and validation. The Electronic System Level (ESL) methodology and Virtual Prototypes (VPs) have paved the way for efficient SoC development. VPs are executable specifications and prototypes of an SoC before the Hardware (HW) is developed, allowing engineers to develop Software (SW) and perform verification tasks before HW prototypes are available. However, the abstraction that enables fast simulation speeds in VPs also omits important information about the system performance or limits understanding the SoC's interaction with its environment. This has formed new gaps between the layers of abstraction that require new techniques to handle future demand in improved development techniques for SoCs. This thesis identifies such gaps and discusses emerging research questions around the methodologies and gaps between layers of abstractions. Based on a combined Register-Transfer level (RTL) and VP description, several approaches for modeling, optimization, and verification are presented. Through the presented approaches, this thesis demonstrates how the identified gaps between layers of abstraction can be bridged to reach a holistic development flow for modern SoC designs