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Glacial dynamics of the Laurentide Ice Sheet along a land-to-sea transect in East Canada
Get PDFThe Labrador Sea is a pivotal region for the climate system of Earth, as it is home to the Atlantic Meridional Overturning Circulation (AMOC) current. The AMOC has been influenced by the growth and decay of large ice sheets on both shores of the Labrador Sea during the Quaternary period. This thesis focuses on the glacial dynamics of the Laurentide Ice Sheet (LIS) in East Canada during the Late Pleistocene era. A more comprehensive understanding of the LIS facilitates future prediction of changes and influences exerted by the Greenland Ice Sheet. A land-to-sea approach is employed, with two distinct working areas being considered: the terrestrial Lake Manicouagan (Manikuakan, according to Innu toponymy) and the marine Labrador Shelf. This transect follows the chronology of retreat of the LIS. In this thesis, marine geophysical datasets, mainly 2D multi-channel seismic reflection profiles, are interpreted. In particular, the sedimentary sequence of Lake Manicouagan is delineated for the first time using one of the seismic reflection datasets, and the thickness of this sequence is estimated. Furthermore, this thesis describes for the first time potential interglacial sediments that are part of two preserved glacial cycles present on the Labrador Shelf. The reconstruction of the ice margin and dynamics of the LIS during the Late Pleistocene era is facilitated by the use of glacial landforms on the Labrador Shelf. The discovery of subglacial channels and grounding-zone wedges (GZWs) has enabled a more comprehensive understanding of the past behaviour of the LIS. The results of this research highlight the potential of both Lake Manicouagan and the Labrador Shelf as rich paleoclimate archives. These regions have the potential to reveal important information during future drilling campaigns about environmental parameters of the Late Pleistocene from a region that is key for the planet's climate system
Applikation der Finite-Elemente Methode auf die grenzflächenkontrollierte Schädigung von Leichtmetalllegierungen
Get PDFDamage to interfaces between light-metal alloys and solid structures or liquid environments is a critical topic, given the widespread use of these materials in lightweight construction, automotive, and aeronautical applications. Therefore, the development of models to describe the relevant physicochemical phenomena via computationally aided simulations is of great scientific and industrial interest. In this thesis, the applicability of Finite Element Method on three different damage scenarios of aluminum (AA1050), titanium (cpTi), and magnesium (cpMg) structures with their respective protecting oxide layers is evaluated to gain mechanistic insights and predictive capabilities. The utilized method includes the implicit implementation of the oxide layers via manipulation of boundary conditions, which allows simulating macroscale geometries but include microscale effects
Deletion of the microbially regulated enzyme hexokinase 2 in intestinal epithelial cells protects from intestinal inflammation and cell death
Get PDFUpregulation of glycolytic enzymes as well as glycolysis in general has been observed in a plethora of immune cells and some non-immunological cells. In our study, we show upregulation of the glycolytic pace-maker enzyme Hexokinase 2 (HK2) in intestinal epithelial cells (IECs) upon intestinal inflammation and inflammatory bowel disease (IBD). In accordance with this observation, deletion of Hk2 in IECs specifically conferred protection upon acute colitis. Moreover, deletion of Hk2 in IECs did not entail any negative consequences regarding whole body glucose homeostasis or glycolytic function in IECs suggesting IEC-specific ablation of Hk2 as safe. Functionally, we show that the mechanism of how loss of Hk2 ameliorates inflammation is not attributed to a role in glycolysis. Instead, our study provides evidence that loss of Hk2 leads to reduced intestinal epithelial cell death. We propose that mechanistically, this effect is facilitated by downregulation of Peptidyl-prolyl cis-trans isomerase (Ppif) which is critically involved in mitochondria-mediated cell death via the mitochondrial permeability transition pore (mPTP). In line with this we observed a lower mitochondrial membrane permeability and reduced markers of mitochondria-mediated cell death following deletion of Hk2 in IECs. We therefore propose HK2 as a novel target for IBD and intestinal inflammation in general
AuTiO2 vs. TiO2 – In-vitro Vergleich von nanostrukturierten goldbeschichteten Titanoberflächen mit klassischem TiO2 bezüglich Biokompatibilität und Wachstumsverhalten von Osteoblasten
Get PDFTitan ist seit seiner Einführung als Biomaterial vor über 50 Jahren meistens Implantatwerkstoff der ersten Wahl. Eine einzigartige Kombination aus mechanischen und biologischen Eigenschaften sind die Hauptvorteile gegenüber alternativen Materialien. Dennoch gibt es Optimierungspotenzial, weswegen vor allem an der Materialoberfläche geforscht wird. Nanotechnologie eröffnet dabei neue Möglichkeiten der Oberflächenbeschichtung. Goldnanopartikel (AuNPs) werden bereits vielfältig in der Medizin eingesetzt, insbesondere dank guter Zellaufnahme, Biokompatibilität und osseogenem Potenzial. Mithilfe eines innovativen Herstellungsprozesses wurde eine neuartige Au-TiO2-Oberfläche hergestellt, die mit konventionellem TiO2 und einer neutralen Kontrolle (Glas) verglichen wurde. Osteoblastenkulturen wurden auf den Platten kultiviert und MTT-, BrdU-Tests sowie Laserfluoreszenzmikroskopie (FDA/PI-Färbung) und REM zur Beurteilung der Biokompatibilität und Zellmorphologie durchgeführt. Untersuchungszeitpunkte lagen bei 12 und 24 Stunden. Die Oberflächenanalyse zeigte am REM AuNPs mit blütenartiger Mikrostruktur (2-5 µm), die wiederum aus kleineren Unterstrukturen mit Durchmessern im Nanometerbereich bestehen, sowie Nanocracks und säulenartige Kornstrukturen. Kontaktwinkelmessungen bescheinigten dem Au-TiO2 eine Superhydrophilität mit CA <5°. Die Au-TiO2-Oberfläche erzielte die besten Ergebnisse hinsichtlich Zellproliferation und -viabilität. Die Mikroskopie zeigte außerdem, dass Anzahl und Länge der Filopodien und Zell-zu-Zell-Kontakte im Vergleich zu TiO2 wesentlich größer waren. Die Zellformen erschienen deutlich regelmäßiger im Vergleich. Es konnten auch Zell-zu-Oberflächen-Kontakte ausgebildet werden, ein Hinweis auf Bioaktivität
Assessing sediment toxicity risks with bioavailable metal fractions: new factors and index applied to the Colombian tropical Andes hotspot
Get PDFHeavy metal toxicity risk assessments in sediments often rely on pseudototal concentrations, despite the higher theoretical predictive potential of bioavailable fractions. This study introduces the Bioavailable Fraction Toxicity Factor (BTf) and the Bioavailable Fraction Toxicity Index (BTI) to evaluate metal toxicity risks using a bioavailable fraction calculated as the sum of the first two steps of the Tessier sequential extraction procedure. Investigating heavy metal pollution (Cd, Cr, Cu, Mn, Ni, Pb, Zn) in the Vetas River catchment, a critical freshwater source in the Santurbán Páramo within the Tropical Andes biodiversity hotspot, the study identified artisanal and small-scale mining as the primary driver of contamination. Water and sediment of mining areas, particularly La Baja Creek and El Volcán Village, exhibited the highest concentrations of metals, with some sediment levels being categorized as strongly contaminated by the Geoaccumulation Index and Pollution Load Index and exceeding the Probable Effect Concentration threshold. Bioavailable fraction of metals in sediments were measured. Bioavailable fractions were higher in mining-affected areas, suggesting greater potential for metal release under acidic conditions. The BTf and BTI provided a more nuanced understanding of metal toxicity risks compared to pseudototal concentrations, with higher BTI values in mining-influenced sites. These findings underscore the need for mitigation measures to address heavy metal pollution and highlight the ecological importance of the Santurbán Páramo. Further research into bioremediation potential using local flora is recommended to support sustainable management practices
Ultra-processed foods and plant-based alternatives impair nutritional quality of omnivorous and plant-forward dietary patterns in college students
Get PDFThe health benefits of a plant-based diet may be outweighed by an increased consumption of ultra-processed foods (UPF) and plant-based alternatives. This study compares diet quality (intakes of protein, saturated fatty acids, sugar, fiber, and micronutrients) and nutritional status (prevalence of low holotranscobalamin and ferritin levels) among different dietary patterns: 22.5% vegans, 46.5% vegetarians, 31% omnivores in 142 first-year college students (20 ± 1.6 years, BMI 21.9 ± 3.1 kg/m², 83% female). Intakes of vitamin B12, folate, iron, zinc, and calcium were on average below reference values, especially in vegans and vegetarians. However, the prevalence of low holotranscobalamin and ferritin levels did not differ between the dietary groups, presumably due to supplementation. Irrespective of the diet, UPF contributed to 49% of daily energy intake. UPF exhibited a lower content of protein, fiber, vitamin B2, vitamin B12, folate, zinc and calcium compared to processed foods (all p < 0.001). Plant-based alternatives contained more fiber and less saturated fatty acids whereas the content of protein and micronutrients was lower compared with animal products (all p < 0.05). In conclusion, UPF consumption contributes to the inadequate intake of many micronutrients by young adults. This is further aggravated by plant-forward eating patterns including the consumption of plant-based alternatives
Comparison of derivative-based and correlation-based methods to estimate effective connectivity in neural networks
Get PDFInferring and understanding the underlying connectivity structure of a system solely from the observed activity of its constituent components is a challenge in many areas of science. In neuroscience, techniques for estimating connectivity are paramount when attempting to understand the network structure of neural systems from their recorded activity patterns. To date, no universally accepted method exists for the inference of effective connectivity, which describes how the activity of a neural node mechanistically affects the activity of other nodes. Here, focussing on purely excitatory networks of small to intermediate size and continuous node dynamics, we provide a systematic comparison of different approaches for estimating effective connectivity. Starting with the Hopf neuron model in conjunction with known ground truth structural connectivity, we reconstruct the system's connectivity matrix using a variety of algorithms. We show that, in sparse non-linear networks with delays, combining a lagged-cross-correlation (LCC) approach with a recently published derivative-based covariance analysis method provides the most reliable estimation of the known ground truth connectivity matrix. We outline how the parameters of the Hopf model, including those controlling the bifurcation, noise, and delay distribution, affect this result. We also show that in linear networks, LCC has comparable performance to a method based on transfer entropy, at a drastically lower computational cost. [...] Our results show that a comparatively simple method can be used to reliably estimate directed effective connectivity in sparse neural systems in the presence of spatio-temporal delays and noise. We provide concrete suggestions for the estimation of effective connectivity in a scenario common in biological research, where only neuronal activity of a small set of neurons, but not connectivity or single-neuron and synapse dynamics, are known
Real‐Time Forecasting Using Mixed‐Frequency VARs With Time‐Varying Parameters
Get PDFThis paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying parameter vector autoregressive model with stochastic volatility. Monte Carlo simulation shows that the novel model is well-suited to estimate missing monthly observations in an environment that is subject to parameter instability. In a real-time forecast exercise, the model delivers accurate now- and forecasts and, on average, outperforms its competitors. Particularly, inflation and unemployment rate forecasts are more precise
Methodological Considerations for the Use of Acid-Based Pre-Treatment Protocols for Carbon and Oxygen Analysis of Tooth Enamel
Get PDFChemical pre-treatment is a common methodological step aimed to remove exogenous materials introduced to archaeological tooth enamel in the burial environment through diagenetic processes. However, some of these methods, involving the use of oxidising reagents such as NaClO, H2O2, as well as weak acids like CH3COOH, have been shown to alter the chemical composition and stable isotope values of enamel. Here, we aim to re-examine the effects of commonly used pre-treatment protocols on bioapatite δ13C and δ18O values, and investigate the relationship between diagenetic alteration and measured isotope values, as indicated by pre-screening using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. Modern and archaeological samples were subjected to 10 commonly used pre-treatment protocols that apply NaClO, H2O2 and/or CH3COOH to tooth enamel powders at treatment lengths. Preservation status and diagenetic alteration prior to and after treatment were investigated using ATR-FTIR. δ13C and δ18O values were measured before and after treatment to determine if different wet chemistry protocols induced isotopic shifts. The results show that all pre-treatment protocols imparted shifts in δ13C and δ18O values of up to ± 1.5‰ in both archaeological and modern samples. Most treated samples display increased crystallinity, likely indicating sample recrystallisation. We suggest that these changes indicate the removal of contamination and diagenetic alteration, and also the dissolution and restructuring of enamel carbonate leading to changes in the in vivo isotope signal. We discourage the use of H2O2 and NaClO to remove organic matter from samples as it incurs unwanted changes to the enamel structure and carbon and oxygen [...
Künstliche Intelligenz zur Förderung von Inklusion: Perspektiven für eine inklusive Bildung im schulischen Kontext
Get PDFDie Masterarbeit Künstliche Intelligenz zur Förderung von Inklusion: Perspektiven für eine inklusive Bildung im schulischen Kontext untersucht, wie KI-basierte Anwendungen zur assistiven und adaptiven Unterstützung von Schüler*innen mit besonderem Förderbedarf eingesetzt werden können. Ziel ist es, Potenziale und Grenzen dieser Technologien im schulischen Alltag sichtbar zu machen. Dabei werden sechs ausgewählte Anwendungen analysiert – drei assistive Technologien und drei adaptive Lernsysteme –, die exemplarisch aufzeigen, wie KI Lernprozesse individualisieren, kommunikative Teilhabe ermöglichen und inklusive Unterrichtsstrukturen unterstützen kann. Aufgrund der bislang geringen empirischen Evidenz stützt sich die Arbeit sowohl auf wissenschaftliche Literatur als auch auf Herstellerdokumentationen und einzelne Fallstudien. Die Ergebnisse verdeutlichen, dass KI-Technologien erhebliche Chancen für eine differenzierende und barrierefreie Bildung eröffnen, zugleich aber technische, organisatorische und ethische Herausforderungen bestehen. Besonders relevant ist die Frage, wie Lehrkräfte auf die Nutzung dieser Systeme vorbereitet werden können und welche Rahmenbedingungen erfüllt sein müssen, damit KI zu mehr Inklusion beiträgt, ohne neue Exklusionen zu erzeugen.The master’s thesis Artificial Intelligence for Promoting Inclusion: Perspectives for Inclusive Education in the School Context examines how AI-based applications can be used to provide assistive and adaptive support to students with special needs. The aim is to highlight the potential and limitations of these technologies in everyday school life. Six selected applications are analyzed – three assistive technologies and three adaptive learning systems – which exemplify how AI can individualize learning processes, enable communicative participation, and support inclusive teaching structures. Due to the limited empirical evidence available to date, the thesis draws on scientific literature as well as manufacturer documentation and individual case studies. The results show that AI technologies open up significant opportunities for differentiated and barrier-free education, but that technical, organizational, and ethical challenges remain. Of particular relevance is the question of how teachers can be prepared for the use of these systems and what conditions must be met for AI to contribute to greater inclusion without creating new forms of exclusion