133798 research outputs found
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Untersuchung von Trockenstress und Waldbränden anhand von Sentinel-2 Daten unter Berücksichtigung verschiedener spektraler Indizes im Nationalpark Pollino (Italien) im Sommer 2017
No full textFabio Adrián Sánchez BurchardtAbstract in englischer SpracheMasterarbeit Universität Innsbruck 202
Tectonics / Late Jurassic initial development of a salt‐dominated fold‐and‐thrust belt: The inverted passive margin of the Eastern Alps (Austria)
No full textThe Northern Calcareous Alps (Eastern Alps, Austria) represent a well‐preserved example of the early stages of inversion of a salt‐bearing passive margin, which occurred in a fully submarine setting. Late Jurassic shortening led to widespread thrusting and folding that nucleated preferentially, although not exclusively, along salt structures developed during the Triassic passive‐margin stage. The presence of a highly effective basal décollement permitted the propagation of deformation without generalized uplift in the area, which was limited to thrusts, folds and squeezed salt structures. The development of individual structures was controlled by the orientation of pre‐existing salt structures, the thickness of supra‐salt stratigraphy, the lateral propagation of deformation, and, possibly, the redistribution of salt within salt structures prior to contraction and the influence of sub‐salt basement faults. Syn‐tectonic sediments make it possible to reliably reconstruct the timing of structural inversion. These same sediments were in turn controlled by structural evolution, with depocenters developing roughly parallel to the inverting structures. The structures documented here are evidence for Late Jurassic shortening across the central Eastern Alps, totaling a few to few tens of kilometers. This is the first systematic description of structures of Late Jurassic age in the Eastern Alps and provides a framework within which to understand the abundance of syn‐tectonic deposits of this age in the area. Particular attention is paid to the Totengebirge–Trattberg contractional system, an outstandingly long set of structures, whose continuity and significance has gone previously unrecognized.Österreichische Forschungsförderungsgesellschaft ETAPAS (FO999888049)Fonds zur Förderung der Wissenschaftlichen Forschung 10.55776/I5399Version of recor
Environmental Microbiology / Insights Into Phylogeny, Diversity and Functional Potential of Poseidoniales Viruses
No full textViruses infecting archaea play significant ecological roles in marine ecosystems through host infection and lysis, yet they have remained an underexplored component of the virosphere. In this study, we recovered 451 archaeal viruses from a subtropical estuary, identifying 63 that are associated with the dominant marine order Poseidoniales (Marine Group II Archaea). Phylogenetic analyses of a subset of complete and nearly-complete viral genomes assigned these viruses to the order Magrovirales, a lineage of Poseidoniales viruses, and identified a novel group of viruses distinct from Magrovirales. Utilising demarcation criteria established for the classification of archaeal tailed viruses, we propose two families within the order Magrovirales: Apasviridae (magrovirus group A), comprising the genera Agnivirus and Savitrvirus, and Krittikaviridae (magrovirus group E) encompassing the genus Velanvirus. Additionally, we propose a new order, distinct from Magrovirales, named Adrikavirales, which includes the genus Vyasavirus. Our detailed genomic characterisation of the new viral lineages revealed genes involved in viral assembly and egress, such as those responsible for creating holin rafts to lyse host cell membranes, a feature predominantly known from bacteriophages. Furthermore, we identified a broad spectrum of auxiliary metabolic genes, suggesting that these viruses can modulate host metabolism. Collectively, our findings substantially enhance the current understanding of the diversity and functional potential of Poseidoniales viruses.Version of recor
Behavioral Variation in the Circadian Rhythm and Locomotor Activity of Drosophila nigrosparsa
No full textMasterarbeit Universität Innsbruck 202
Analyzing the performance of digital platform strategies using company news
No full textThis thesis examines the financial impact of digital platform announcements on incumbent companies, addressing three key research questions: (1) Do digital platform strategies contribute to the performance of incumbent companies, as suggested by the current state of the literature? (2) Is there a positive correlation between the adoption of a digital platform strategy and a company's financial performance? (3) Do different types of digital platform strategies (e.g., innovation vs. transaction platforms) have varying impacts on company performance? To explore these questions, the study categorizes platform announcements into two types: (1) Strategy Type Announcements, such as new platform launches, acquisitions, and collaborations; and (2) Platform Type Announcements, distinguishing between "innovation" and "transaction" platforms. Using event study methodologies and statistical tests (e.g., BMP, KP, and GRANK), cumulative average abnormal returns (CAAR) were analyzed across various event windows using the MXOW and MXWD indices to capture market reactions.
Our research contributes to the current literature on digital platforms in two key ways. First, it examines the effects of digital platform announcements, revealing that such announcements often generate positive short-term financial reactions, particularly for transaction platform launches or collaborations. However, the positive impact tends to decline within a day, suggesting the influence of external factors or challenges in realizing the benefits. Conversely, announcements of innovation platforms or platform enhancements frequently resulted in negative market reactions, possibly due to concerns about governance, openness, or resource availability.
Second, the study emphasizes the significant influence of internal and external factors—such as platform governance, openness, technology type, firm size, regulatory environment, and data privacy laws—on shaping market responses to platform announcements. While the research provides valuable insights, it is limited by its focus on short-term reactions, reliance on global indices, and a p-value threshold of 0.1. Future research could address these limitations by exploring longer-term impacts, regional dynamics, and qualitative analyses to better understand the drivers of market reactions to platform announcements.from Tareq BallanMasterarbeit University of Innsbruck 202
Metabarcoding and Metagenomics / Inter-laboratory ring test for environmental DNA extraction protocols: implications for marine megafauna detection using three novel qPCR assays
No full textThe comparability of methods applied to environmental DNA (eDNA) samples across laboratories remains a significant challenge for biodiversity monitoring on a global scale. Performance differences between protocols can jeopardize effective conservation strategies across regions and focal species. To address potential discrepancies amongst four international partners within a collaborative eDNA initiative, an inter-laboratory comparison (i.e., ring test) was conducted to compare efficiencies of established DNA extraction methodologies based on 39 eDNA samples. Each laboratory contributed eight to eleven samples collected throughout the North-East Atlantic and the Mediterranean Sea near sperm whales, porbeagle sharks, basking sharks, bottlenose dolphins and common dolphins. After lysis, aliquots were exchanged between laboratories before subsequent DNA extraction using each facility’s preferred method. Extracts were returned to the lysates’ respective laboratories of origin for measurements of total DNA concentration, as well as quantitative PCR using three novel species-specific assays for marine megafauna. Our findings revealed similar concentrations of total DNA, yet a significant reduction in extraction performance for targeted qPCR reactions by one laboratory, who has therefore modified their extraction method to be used for the remainder of this project. Overall, detection success differed based on the target taxa with sharks being less often detected (and at lower concentrations) than marine mammals. Significant interaction effects were found between combinations of laboratories and species, suggesting a link between extraction protocols and variable environmental conditions. Our study serves as a foundational step towards establishing reproducible practices that are crucial for the success of multinational eDNA projects to enable comparable results.Europäische Kommission 101052342Fonds zur Förderung der Wissenschaftlichen Forschung (DE-588)2054142-9 10.55776/I638Version of recor
Chlorophyllkataboliten in Lebermoosen : am Beispiel von Conocephalum salebrosum
No full textMasterarbeit Universität Innsbruck 202
Der Arbeitsalltag von Lehrpersonen der Sekundarstufe I in Tirol unter den Bedingungen der COVID-19-Krise : eine qualitative Erhebung über Belastungen, Herausforderungen, Bewältigungsmöglichkeiten und den Gewinn für die Bildungsaufgabe selbstreguliertes Lernen
No full textDiese Masterarbeit analysiert das Erleben des Arbeitsalltags von Lehrpersonen der Sekundar-stufe I während der COVID-19-Krise. Die subjektiven Sichtweisen auf neue Anforderungen, Belastungen und Herausforderungen sowie Bewältigungsmöglichkeiten und neue Chancen in Bezug auf das Konzept des selbstregulierten Lernens stehen im Mittelpunkt. Da die COVID-19-Krise einen großen Einfluss auf den Bildungsbereich der Sekundarstufe I hatte, leistet diese Forschung mit ihren praxisorientierten Erkenntnissen einen wichtigen Beitrag zur Bildungsforschung in Krisenzeiten und ist somit sowohl von wissenschaftlichen als auch von gesellschaftstheoretischem Interesse.
Im theoretischen Teil wird zunächst ein historischer Abriss der COVID-19-Krise und deren Auswirkungen auf die Mittelschulen in Tirol gegeben. Anschließend folgt eine Darstellung der Belastungsfaktoren im Berufsalltag von Lehrpersonen. In diesem Zusammenhang werden verschiedene theoretische Modelle beschrieben, welche belastende Gegebenheiten am Arbeitsplatz und deren negativen Auswirkungen auf die Arbeitskraft sowie grundlegende Prozesse sowie Supervision als präventive Maßnahme zur Unterstützung von Lehrpersonen thematisiert. Darüber hinaus wird auf das Konzept des selbstregulierten Lernens eingegangen, dessen Kompetenzen insbesondere während der COVID-19-Krise gefordert waren und eine entscheidende Grundlage für den lebenslangen selbstständigen Bildungserwerb bilden.
Der empirische Teil dient der Beantwortung der Forschungsfragen. Dafür wurden sieben leitfadengestützte Experteninterviews mit Lehrpersonen der Sekundarstufe I geführt. Die Auswertung erfolgt mittels qualitativer Inhaltsanalyse nach Kuckartz (2010, 2018). Die Ergebnisse zeigen, dass der „neue“ Arbeitsalltag zunehmend als herausfordernd wahrgenommen wird. Es konnten sowohl neue Erkenntnisse zu Herausforderungen und Belastungen im Arbeitsalltag festgestellt als auch bereits bekannte bestätigt werden. Die Bewältigungsmöglichkeiten der Lehrpersonen erwiesen sich als ausreichend, jedoch könnten ungenutzte Ressourcen noch gezielter ausgeschöpft werden. Verbesserungsansätze zeigen sich im Bereich des selbstregulierten Lernens sowie auf bildungspolitischer Ebene, wo Handlungsbedarf besteht, um Lehrpersonen zu entlasten und das Schulleben durch klare Strukturen einheitlicher und gerechter für alle Bildungsbeteiligten zu gestalten.This master's thesis analyzes the experiences of secondary school teachers during the COVID-19 crisis, focusing on their perspectives regarding new demands, burdens, and chal-lenges, as well as coping strategies and emerging opportunities related to the concept of self-regulated learning. Given the significant impact of the COVID-19 crisis on secondary educa-tion, this research offers valuable practice-oriented insights, contributing to educational re-search in times of crisis and holding both scientific and societal relevance.
The theoretical section provides a historical overview of the COVID-19 crisis and its effects on secondary schools in the Tyrol.
It then explores the stress factors in the professional lives of teachers, describing various the-oretical models that address workplace challenges and their negative impact on pedagogues’ well-being as well as presenting Supervision as a preventive measure to support teachers.
Additionally, the concept of self-regulated learning is examined, focusing on how its compe-tencies, which were particularly demanded during the COVID-19 crisis, form a crucial foun-dation for lifelong, autonomous learning.
In the empirical section, the research question is addressed through seven guided expert in-terviews with secondary school teachers. The data were analyzed using Kuckartz’s qualita-tive content analysis. The findings reveal that the “new” working conditions are increasingly perceived as challenging. New insights into the challenges and burdens of teachers’ work were identified and previously known factors confirmed. The coping strategies of teachers proved to be generally adequate, though untapped resources could be utilized more effective-ly. Areas for improvement were identified in the domain of self-regulated learning and at an educational policy level, where action is needed to relieve teachers and to use clear struc-tures to create a more consistent and a juster school environment for all people involved.eingereicht von Lisa Kraker-Haller, BA, BEdAbstract in englischer SpracheMasterarbeit Universität Innsbruck 202
Episodischer Abfluss im oberen Brixenbachtal : Auslösefaktoren oberirdischen Abflusses im Bereich Talkaser Niederleger und dessen Auswirkungen auf den Durchfluss am Pegel Brixen im Thale
No full textJan SchmidtMasterarbeit Universität Innsbruck 202
Light Detection and Ranging
No full textAlpin-nivale Ökosysteme verändern sich aufgrund des Klimawandels rasant, wodurch der Bedarf an verbesserten Methoden zur Vegetationsüberwachung steigt. Traditionelle feldbasierte Ansätze liefern wertvolle langfristige Biodiversitätsdaten, sind jedoch räumlich begrenzt. Fernerkundung bietet eine skalierbare Alternative mit erhöhter räumlicher und zeitlicher Abdeckung. Während großflächige Vegetationsveränderungen gut erfasst werden können, bleibt die feingranulare (FG) Klassifikation alpiner und nivale Vegetation eine Herausforderung. Deep-Learning-Ansätze wie Convolutional Neural Networks (CNNs) zeigen zwar Potenzial für FG-Klassifikationen, erfordern jedoch große, qualitativ hochwertige Trainingsdatensätze, was ihre Anwendung in alpin-nivalen Umgebungen unpraktisch macht. Aus diesem Grund untersucht diese Arbeit die Eignung des Random-Forest-(RF)-Algorithmus für die FG-Klassifikation auf Basis hochauflösender Multispektralbilder (MI), aus LiDAR abgeleiteter struktureller Features und in-situ Vegetationsdaten aus dem MICROCLIM-Projekt am Schrankogel, Tirol, Österreich. Ein hierarchischer Clusterings-Ansatz wurde angewendet, um FG-Vegetationsklassen schrittweise zu größeren ökologischen Kategorien zusammenzuführen. Dadurch konnte die Modellleistung auf unterschiedlichen Granularitätsebenen bewertet und bestimmt werden, ab welchem Aggregationsniveau sinnvolle Klassifikationsergebnisse erzielt werden. Zusätzlich wurde der Einfluss der Datenfusion untersucht, indem die Modellleistung von MI allein mit MI in Kombination mit LiDAR-Features verglichen wurde. Die Ergebnisse zeigen, dass RF bei der feingranularen Klassifikation (11 Vegetationsklassen, Makro-F1-Score = 38,1 %) erhebliche Schwierigkeiten hat. Hohe Fehlklassifikationsraten resultieren aus spektraler Überlappung, intra-klassen Variabilität und Klassenungleichgewicht. Die Klassifikationsleistung verbessert sich jedoch deutlich, wenn Vegetationsklassen zu breiteren Kategorien zusammengefasst werden. Ab einer Klassifikation mit fünf Klassen wurden erstmals sinnvolle Ergebnisse erzielt (Makro-F1-Score > 60 %). Die Integration von LiDAR-Features führte insbesondere bei strukturell unterschiedlichen Vegetationstypen in der subnivalen und nivalen Zone zu einer etwa 10%igen Verbesserung der Klassifikationsgenauigkeit. Auf gröberen Klassifikationsebenen trägt LiDAR jedoch kaum zur Verbesserung bei, da strukturelle Unterschiede weniger relevant werden. Diese Ergebnisse deuten darauf hin, dass das in dieser Arbeit verwendete RF-Modell für die feingranulare alpin-nivale Vegetationsklassifikation nur bedingt geeignet ist, sich jedoch für breitere ökologische Gruppierungen als effektiv erweist. Zukünftige Forschung sollte alternative Machine-Learning-Ansätze, verbesserte Feature-Selection-Methoden und erweiterte Datensätze in räumlicher und/oder zeitlicher Hinsicht untersuchen, um die Klassifikationsgenauigkeit in der alpinen Vegetationskartierung zu verbessern.Alpine-Nival environments are changing rapidly due to climate change, increasing the need for improved vegetation monitoring methods. Traditional field-based approaches provide valuable long-term biodiversity data but are spatially limited. Remote sensing offers a scalable alternative with enhanced spatial and temporal coverage. However, while large-scale vegetation changes can be well captured, fine-grained (FG) alpine-nival vegetation classification remains a challenge due to spectral similarity among vegetation types, intra-class variability, and data limitations in remote high-altitude environments. While deep learning approaches like Convolutional Neural Networks (CNNs) show promise for FG classification, their reliance on large, high-quality training datasets makes them impractical for alpine-nival applications. As an alternative, this thesis evaluates the suitability of the Random Forest (RF) algorithm for FG classification using high-resolution multispectral imagery (MI), LiDAR-derived structural features, and in-situ vegetation data from the MICROCLIM project at Mount Schrankogel, Tyrol, Austria. A hierarchical clustering framework was applied to systematically merge FG vegetation classes into broader ecological categories, allowing an assessment of classification performance across different granularities to determine at which level classifications become meaningful. This thesis also examines the impact of data fusion by comparing model performance using MI alone versus MI combined with LiDAR-derived features. The results indicate that RF struggles with fine-grained classification (11 vegetation classes, Macro F1-score = 38.1%), with high misclassification rates driven by spectral overlap, intra-class variability, and class imbalance. Performance improves significantly when vegetation classes are aggregated into broader categories, with meaningful classification results (Macro F1-score >60%) first observed at a five-class level. The integration of LiDAR features improves classification accuracy by approximately 10% in fine-grained classifications, particularly for structurally distinct vegetation classes in the subnival and nival zones. However, at broader classification levels, LiDAR contributes little to the classification task, as structural differences become less relevant. These findings suggest that while the RF model employed in this thesis is not well-suited for fine-grained alpine-nival vegetation classification, it remains effective for broader ecological groupings. Future research should explore alternative machine learning approaches, improved feature selection methods, and expanded datasets spatially and/or temporally to enhance classification accuracy in alpine vegetation mapping.by Stefan Angerer, B.Sc.Zusammenfassung in deutscher SpracheMasterarbeit University Innsbruck 202