1,916 research outputs found
Robustness, Heterogeneity and Structure Capturing for Graph Representation Learning and its Application
Graph neural networks (GNNs) are potent methods for graph representation learn- ing (GRL), which extract knowledge from complicated (graph) structured data in various real-world scenarios. However, GRL still faces many challenges. Firstly GNN-based node classification may deteriorate substantially by overlooking the pos- sibility of noisy data in graph structures, as models wrongly process the relation among nodes in the input graphs as the ground truth. Secondly, nodes and edges have different types in the real-world and it is essential to capture this heterogeneity in graph representation learning. Next, relations among nodes are not restricted to pairwise relations and it is necessary to capture the complex relations accordingly. Finally, the absence of structural encodings, such as positional information, deterio- rates the performance of GNNs. This thesis proposes novel methods to address the aforementioned problems:
1. Bayesian Graph Attention Network (BGAT): Developed for situations with scarce data, this method addresses the influence of spurious edges. Incor- porating Bayesian principles into the graph attention mechanism enhances robustness, leading to competitive performance against benchmarks (Chapter 3).
2. Neighbour Contrastive Heterogeneous Graph Attention Network (NC-HGAT): By enhancing a cutting-edge self-supervised heterogeneous graph neural net- work model (HGAT) with neighbour contrastive learning, this method ad- dresses heterogeneity and uncertainty simultaneously. Extra attention to edge relations in heterogeneous graphs also aids in subsequent classification tasks (Chapter 4).
3. A novel ensemble learning framework is introduced for predicting stock price movements. It adeptly captures both group-level and pairwise relations, lead- ing to notable advancements over the existing state-of-the-art. The integration of hypergraph and graph models, coupled with the utilisation of auxiliary data via GNNs before recurrent neural network (RNN), provides a deeper under- standing of long-term dependencies between similar entities in multivariate time series analysis (Chapter 5).
4. A novel framework for graph structure learning is introduced, segmenting graphs into distinct patches. By harnessing the capabilities of transformers and integrating other position encoding techniques, this approach robustly capture intricate structural information within a graph. This results in a more comprehensive understanding of its underlying patterns (Chapter 6)
Pristup specifikaciji i generisanju proizvodnih procesa zasnovan na inΕΎenjerstvu voΔenom modelima
In this thesis, we present an approach to the production process specification and generation based on the model-driven paradigm, with the goal to increase the flexibility of factories and respond to the challenges that emerged in the era of Industry 4.0 more efficiently. To formally specify production processes and their variations in the Industry 4.0 environment, we created a novel domain-specific modeling language, whose models are machine-readable. The created language can be used to model production processes that can be independent of any production system, enabling process models to be used in different production systems, and process models used for the specific production system. To automatically transform production process models dependent on the specific production system into instructions that are to be executed by production system resources, we created an instruction generator. Also, we created generators for different manufacturing documentation, which automatically transform production process models into manufacturing documents of different types. The proposed approach, domain-specific modeling language, and software solution contribute to introducing factories into the digital transformation process. As factories must rapidly adapt to new products and their variations in the era of Industry 4.0, production must be dynamically led and instructions must be automatically sent to factory resources, depending on products that are to be created on the shop floor. The proposed approach contributes to the creation of such a dynamic environment in contemporary factories, as it allows to automatically generate instructions from process models and send them to resources for execution. Additionally, as there are numerous different products and their variations, keeping the required manufacturing documentation up to date becomes challenging, which can be done automatically by using the proposed approach and thus significantly lower process designers' time.Π£ ΠΎΠ²ΠΎΡ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½ ΡΠ΅ ΠΏΡΠΈΡΡΡΠΏ ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡΠΈ ΠΈ Π³Π΅Π½Π΅ΡΠΈΡΠ°ΡΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° Π·Π°ΡΠ½ΠΎΠ²Π°Π½ Π½Π° ΠΈΠ½ΠΆΠ΅ΡΠ΅ΡΡΡΠ²Ρ Π²ΠΎΡΠ΅Π½ΠΎΠΌ ΠΌΠΎΠ΄Π΅Π»ΠΈΠΌΠ°, Ρ ΡΠΈΡΡ ΠΏΠΎΠ²Π΅ΡΠ°ΡΠ° ΡΠ»Π΅ΠΊΡΠΈΠ±ΠΈΠ»Π½ΠΎΡΡΠΈ ΠΏΠΎΡΡΡΠΎΡΠ΅ΡΠ° Ρ ΡΠ°Π±ΡΠΈΠΊΠ°ΠΌΠ° ΠΈ Π΅ΡΠΈΠΊΠ°ΡΠ½ΠΈΡΠ΅Π³ ΡΠ°Π·ΡΠ΅ΡΠ°Π²Π°ΡΠ° ΠΈΠ·Π°Π·ΠΎΠ²Π° ΠΊΠΎΡΠΈ ΡΠ΅ ΠΏΠΎΡΠ°Π²ΡΡΡΡ Ρ Π΅ΡΠΈ ΠΠ½Π΄ΡΡΡΡΠΈΡΠ΅ 4.0. ΠΠ° ΠΏΠΎΡΡΠ΅Π±Π΅ ΡΠΎΡΠΌΠ°Π»Π½Π΅ ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° ΠΈ ΡΠΈΡ
ΠΎΠ²ΠΈΡ
Π²Π°ΡΠΈΡΠ°ΡΠΈΡΠ° Ρ Π°ΠΌΠ±ΠΈΡΠ΅Π½ΡΡ ΠΠ½Π΄ΡΡΡΡΠΈΡΠ΅ 4.0, ΠΊΡΠ΅ΠΈΡΠ°Π½ ΡΠ΅ Π½ΠΎΠ²ΠΈ Π½Π°ΠΌΠ΅Π½ΡΠΊΠΈ ΡΠ΅Π·ΠΈΠΊ, ΡΠΈΡΠ΅ ΠΌΠΎΠ΄Π΅Π»Π΅ ΡΠ°ΡΡΠ½Π°Ρ ΠΌΠΎΠΆΠ΅ Π΄Π° ΠΎΠ±ΡΠ°Π΄ΠΈ Π½Π° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ Π½Π°ΡΠΈΠ½. ΠΡΠ΅ΠΈΡΠ°Π½ΠΈ ΡΠ΅Π·ΠΈΠΊ ΠΈΠΌΠ° ΠΌΠΎΠ³ΡΡΠ½ΠΎΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° ΠΊΠΎΡΠΈ ΠΌΠΎΠ³Ρ Π±ΠΈΡΠΈ Π½Π΅Π·Π°Π²ΠΈΡΠ½ΠΈ ΠΎΠ΄ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ° ΠΈ ΡΠΈΠΌΠ΅ ΡΠΏΠΎΡΡΠ΅Π±ΡΠ΅Π½ΠΈ Ρ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΠΌ ΠΏΠΎΡΡΡΠΎΡΠ΅ΡΠΈΠΌΠ° ΠΈΠ»ΠΈ ΡΠ°Π±ΡΠΈΠΊΠ°ΠΌΠ°, Π°Π»ΠΈ ΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° ΠΊΠΎΡΠΈ ΡΡ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΈ Π·Π° ΠΎΠ΄ΡΠ΅ΡΠ΅Π½ΠΈ ΡΠΈΡΡΠ΅ΠΌ. ΠΠ°ΠΊΠΎ Π±ΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° Π·Π°Π²ΠΈΡΠ½ΠΈΡ
ΠΎΠ΄ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ° Π±ΠΈΠ»ΠΎ ΠΌΠΎΠ³ΡΡΠ΅ Π½Π° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ Π½Π°ΡΠΈΠ½ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠΈΡΠ°ΡΠΈ Ρ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅ ΠΊΠΎΡΠ΅ ΡΠ΅ΡΡΡΡΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ° ΠΈΠ·Π²ΡΡΠ°Π²Π°ΡΡ, ΠΊΡΠ΅ΠΈΡΠ°Π½ ΡΠ΅ Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠ°. Π’Π°ΠΊΠΎΡΠ΅ ΡΡ ΠΊΡΠ΅ΠΈΡΠ°Π½ΠΈ ΠΈ Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠΈ ΡΠ΅Ρ
Π½ΠΈΡΠΊΠ΅ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡΠ΅, ΠΊΠΎΡΠΈ Π½Π° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ Π½Π°ΡΠΈΠ½ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»Π΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΠ° Ρ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
ΡΠΈΠΏΠΎΠ²Π°. Π£ΠΏΠΎΡΡΠ΅Π±ΠΎΠΌ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠ³ ΠΏΡΠΈΡΡΡΠΏΠ°, Π½Π°ΠΌΠ΅Π½ΡΠΊΠΎΠ³ ΡΠ΅Π·ΠΈΠΊΠ° ΠΈ ΡΠΎΡΡΠ²Π΅ΡΡΠΊΠΎΠ³ ΡΠ΅ΡΠ΅ΡΠ° Π΄ΠΎΠΏΡΠΈΠ½ΠΎΡΠΈ ΡΠ΅ ΡΠ²ΠΎΡΠ΅ΡΡ ΡΠ°Π±ΡΠΈΠΊΠ° Ρ ΠΏΡΠΎΡΠ΅Ρ Π΄ΠΈΠ³ΠΈΡΠ°Π»Π½Π΅ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΡΠ΅. ΠΠ°ΠΊΠΎ ΡΠ°Π±ΡΠΈΠΊΠ΅ Ρ Π΅ΡΠΈ ΠΠ½Π΄ΡΡΡΡΠΈΡΠ΅ 4.0 ΠΌΠΎΡΠ°ΡΡ Π±ΡΠ·ΠΎ Π΄Π° ΡΠ΅ ΠΏΡΠΈΠ»Π°Π³ΠΎΠ΄Π΅ Π½ΠΎΠ²ΠΈΠΌ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠΌΠ° ΠΈ ΡΠΈΡ
ΠΎΠ²ΠΈΠΌ Π²Π°ΡΠΈΡΠ°ΡΠΈΡΠ°ΠΌΠ°, Π½Π΅ΠΎΠΏΡ
ΠΎΠ΄Π½ΠΎ ΡΠ΅ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΈ Π²ΠΎΠ΄ΠΈΡΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡ ΠΈ Π½Π° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ Π½Π°ΡΠΈΠ½ ΡΠ»Π°ΡΠΈ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅ ΡΠ΅ΡΡΡΡΠΈΠΌΠ° Ρ ΡΠ°Π±ΡΠΈΡΠΈ, Ρ Π·Π°Π²ΠΈΡΠ½ΠΎΡΡΠΈ ΠΎΠ΄ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π° ΠΊΠΎΡΠΈ ΡΠ΅ ΠΊΡΠ΅ΠΈΡΠ°ΡΡ Ρ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠΌ ΠΏΠΎΡΡΡΠΎΡΠ΅ΡΡ. Π’ΠΈΠΌΠ΅ ΡΡΠΎ ΡΠ΅ Ρ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠΌ ΠΏΡΠΈΡΡΡΠΏΡ ΠΌΠΎΠ³ΡΡΠ΅ ΠΈΠ· ΠΌΠΎΠ΄Π΅Π»Π° ΠΏΡΠΎΡΠ΅ΡΠ° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ΠΎ Π³Π΅Π½Π΅ΡΠΈΡΠ°ΡΠΈ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅ ΠΈ ΠΏΠΎΡΠ»Π°ΡΠΈ ΠΈΡ
ΡΠ΅ΡΡΡΡΠΈΠΌΠ°, Π΄ΠΎΠΏΡΠΈΠ½ΠΎΡΠΈ ΡΠ΅ ΠΊΡΠ΅ΠΈΡΠ°ΡΡ ΡΠ΅Π΄Π½ΠΎΠ³ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΎΠ³ ΠΎΠΊΡΡΠΆΠ΅ΡΠ° Ρ ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΠΌ ΡΠ°Π±ΡΠΈΠΊΠ°ΠΌΠ°. ΠΠΎΠ΄Π°ΡΠ½ΠΎ, ΡΡΠ»Π΅Π΄ Π²Π΅Π»ΠΈΠΊΠΎΠ³ Π±ΡΠΎΡΠ° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π° ΠΈ ΡΠΈΡ
ΠΎΠ²ΠΈΡ
Π²Π°ΡΠΈΡΠ°ΡΠΈΡΠ°, ΠΏΠΎΡΡΠ°ΡΠ΅ ΠΈΠ·Π°Π·ΠΎΠ²Π½ΠΎ ΠΎΠ΄ΡΠΆΠ°Π²Π°ΡΠΈ Π½Π΅ΠΎΠΏΡ
ΠΎΠ΄Π½Ρ ΡΠ΅Ρ
Π½ΠΈΡΠΊΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡΡ, ΡΡΠΎ ΡΠ΅ Ρ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎΠΌ ΠΏΡΠΈΡΡΡΠΏΡ ΠΌΠΎΠ³ΡΡΠ΅ ΡΡΠ°Π΄ΠΈΡΠΈ Π½Π° Π°ΡΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²Π°Π½ Π½Π°ΡΠΈΠ½ ΠΈ ΡΠΈΠΌΠ΅ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΡΡΡΠ΅Π΄Π΅ΡΠΈ Π²ΡΠ΅ΠΌΠ΅ ΠΏΡΠΎΡΠ΅ΠΊΡΠ°Π½Π°ΡΠ° ΠΏΡΠΎΡΠ΅ΡΠ°.U ovoj disertaciji predstavljen je pristup specifikaciji i generisanju proizvodnih procesa zasnovan na inΕΎenjerstvu voΔenom modelima, u cilju poveΔanja fleksibilnosti postrojenja u fabrikama i efikasnijeg razreΕ‘avanja izazova koji se pojavljuju u eri Industrije 4.0. Za potrebe formalne specifikacije proizvodnih procesa i njihovih varijacija u ambijentu Industrije 4.0, kreiran je novi namenski jezik, Δije modele raΔunar moΕΎe da obradi na automatizovan naΔin. Kreirani jezik ima moguΔnost modelovanja proizvodnih procesa koji mogu biti nezavisni od proizvodnih sistema i time upotrebljeni u razliΔitim postrojenjima ili fabrikama, ali i proizvodnih procesa koji su specifiΔni za odreΔeni sistem. Kako bi modele proizvodnih procesa zavisnih od konkretnog proizvodnog sistema bilo moguΔe na automatizovan naΔin transformisati u instrukcije koje resursi proizvodnog sistema izvrΕ‘avaju, kreiran je generator instrukcija. TakoΔe su kreirani i generatori tehniΔke dokumentacije, koji na automatizovan naΔin transformiΕ‘u modele proizvodnih procesa u dokumente razliΔitih tipova. Upotrebom predloΕΎenog pristupa, namenskog jezika i softverskog reΕ‘enja doprinosi se uvoΔenju fabrika u proces digitalne transformacije. Kako fabrike u eri Industrije 4.0 moraju brzo da se prilagode novim proizvodima i njihovim varijacijama, neophodno je dinamiΔki voditi proizvodnju i na automatizovan naΔin slati instrukcije resursima u fabrici, u zavisnosti od proizvoda koji se kreiraju u konkretnom postrojenju. Time Ε‘to je u predloΕΎenom pristupu moguΔe iz modela procesa automatizovano generisati instrukcije i poslati ih resursima, doprinosi se kreiranju jednog dinamiΔkog okruΕΎenja u savremenim fabrikama. Dodatno, usled velikog broja razliΔitih proizvoda i njihovih varijacija, postaje izazovno odrΕΎavati neophodnu tehniΔku dokumentaciju, Ε‘to je u predloΕΎenom pristupu moguΔe uraditi na automatizovan naΔin i time znaΔajno uΕ‘tedeti vreme projektanata procesa
Unravelling the complex reproductive tactics of male humpback whales : an integrative analysis of paternity, age, testosterone, and genetic diversity
How the underlying forces of sexual selection impact reproductive tactics including elaborate acoustic displays in cetaceans remains poorly understood. Here, I combined 26 years (1995-2020) of photo-identification, behavioural, (epi)genetic, and endocrine data from an endangered population of humpback whales (New Caledonia), to explore male reproductive success, age, physiology, and population dynamics over almost a third of the lifespan of a humpback whale. First, I conducted a paternity analysis on 177 known mother-offspring pairs and confirmed previous findings of low variation in reproductive success in male humpback whales. Second, epigenetic age estimates of 485 males revealed a left-skewed population age structure in the first half of the study period that became more balanced in the second half. Further, older males (> 23 years) more often engaged in certain reproductive tactics (singing and escorting) and were more successful in siring offspring once the population age structure stabilised, suggesting reproductive tactics and reproductive success in male humpback whales may be age-dependent. Third, using enzyme immunoassays on 457 blubber samples, I observed a seasonal decline in male testosterone in the population over the breeding season. Testosterone levels appeared highest during puberty, then decreased and levelled off at the onset of maturity, yet were highly variable at any point during the breeding season and across males of all ages. Lastly, I investigated the influence of genetic diversity at the major histocompatibility complex (MHC) class I and class IIa (DQB and DRB-a) on patterns of male reproductive success in humpback whales. Mating pairs shared fewer alleles than expected under random mating at MHC class I and IIa, thus, providing evidence of an MHC-mediated female mate choice in humpback whales. This thesis provides novel, critical insights into the evolutionary consequences of commercial whaling on the demography, patterns of reproduction and sexual selection of exploited populations of baleen whales."This work was supported by a University of St Andrews School of Biology Ph.D. Scholarship and the Louis M. Herman Research Scholarship 2022 to Franca Eichenberger. Sample collection and analyses from 2018-2020 were supported by grants to Ellen C. Garland (Royal Society University Research Fellowship (UF160081 & URF\R\221020), Royal Society Research Fellows Enhancement Award (RGF\EA\180213), Royal Society Research Grants for Research Fellows 2018 (RGF\R1\181014), National Geographic Grant (#NGS-50654R-18), Carnegie Trust Research Incentive Grant (RIG007772), British Ecological Society Small Research Grant (SR18/1288) and School of Biology Research Committee funding)."--Fundin
The development of bioinformatics workflows to explore single-cell multi-omics data from T and B lymphocytes
The adaptive immune response is responsible for recognising, containing and eliminating viral infection, and protecting from further reinfection. This antigen-specific response is driven by T and B cells, which recognise antigenic epitopes via highly specific heterodimeric surface receptors, termed T-cell receptors (TCRs) and B cell receptors (BCRs). The theoretical diversity of the receptor repertoire that can be generated via homologous recombination of V, D and J genes is large enough (>1015 unique sequences) that virtually any antigen can be recognised. However, only a subset of these are generated within the human body, and how they succeed in specifically recognising any pathogen(s) and distinguishing these from self-proteins remains largely unresolved.
The recent advances in applying single-cell genomics technologies to simultaneously measure the clonality, surface phenotype and transcriptomic signature of pathogen- specific immune cells have significantly improved understanding of these questions. Single-cell multi-omics permits the accurate identification of clonally expanded populations, their differentiation trajectories, the level of immune receptor repertoire diversity involved in the response and the phenotypic and molecular heterogeneity.
This thesis aims to develop a bioinformatic workflow utilising single-cell multi-omics data to explore, quantify and predict the clonal and transcriptomic signatures of the human T-cell response during and following viral infection. In the first aim, a web application, VDJView, was developed to facilitate the simultaneous analysis and visualisation of clonal, transcriptomic and clinical metadata of T and B cell multi-omics data. The application permits non-bioinformaticians to perform quality control and common analyses of single-cell genomics data integrated with other metadata, thus permitting the identification of biologically and clinically relevant parameters. The second aim pertains to analysing the functional, molecular and immune receptor profiles of CD8+ T cells in the acute phase of primary hepatitis C virus (HCV) infection. This analysis identified a novel population of progenitors of exhausted T cells, and lineage tracing revealed distinct trajectories with multiple fates and evolutionary plasticity. Furthermore, it was observed that high-magnitude IFN-Ξ³ CD8+ T-cell response is associated with the increased probability of viral escape and chronic infection. Finally, in the third aim, a novel analysis is presented based on the topological characteristics of a network generated on pathogen-specific, paired-chain, CD8+ TCRs. This analysis revealed how some cross-reactivity between TCRs can be explained via the sequence similarity between TCRs and that this property is not uniformly distributed across all pathogen-specific TCR repertoires. Strong correlations between the topological properties of the network and the biological properties of the TCR sequences were identified and highlighted.
The suite of workflows and methods presented in this thesis are designed to be adaptable to various T and B cell multi-omic datasets. The associated analyses contribute to understanding the role of T and B cells in the adaptive immune response to viral-infection and cancer
2023-2024 Catalog
The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation
Biomaterials for Bone Tissue Engineering 2020
This book presents recent advances in the field of bone tissue engineering, including molecular insights, innovative biomaterials with regenerative properties (e.g., osteoinduction and osteoconduction), and physical stimuli to enhance bone regeneration
Norwegian Hydropower Producersβ Response to the 2021 Energy Price Shock: An Analysis of the Development in the Water Values
Norwegian electricity prices surged during the last half of 2021. A significant increase in the European gas prices and the prices of carbon allowances, low inflow to the reservoirs in southern Norway, and increased demand due to the post-pandemic rebound of economic activity were central drivers for the increase in the electricity price. Soaring prices in thermal energy sources and diminishing water levels in the reservoir have shown how volatile the electricity price can be in a power system that predominantly relies on hydropower. Consequently, understanding how these price determinants influenced the water values of the Norwegian hydropower producers in 2021, will be an important factor to ensure the energy security in the future.
This paper analyses the development of the water values of 17 Norwegian hydropower plants in price areas NO2 and NO5 in the last half of 2021. Through a double censored regression model, the study finds that 71,4 % of the hydropower plants with reliable results had an increasing trend in the water values, while 21,4 % had a decreasing trend. Furthermore, the study analyses how the hydropower producers reacted to the development in the Norwegian and European energy markets. The study finds that 78,6 % of the hydropower producers increased the water values when the gas price increased, and 71,4 % reduced their water values when the European gas storage levels increased. If the carbon spot price increased, 27 % of the hydropower producers increase the water values, while 84,6 % of the producers lowered the water values when the reservoir filling increased.
By applying the rolling window approach to the double censored regression model, we identified potential responses to the market signals for six of the hydropower plants in the study. The responses suggested that the hydropower producers changed their expectations with respect to the market signal, and thus revised their models. The study found that five producers responded in late August and September, while one plant may have had a reaction in November. The evidence suggests that 100 % of the responses indicated a reaction to the European gas storage filling. It was found that 71 % of the responses were associated with the degree of reservoir filling of the hydropower plant. 43 % of the responses could indicate a reaction to the carbon spot price, and 71 % of the responses were associated with a change in expectations of the gas price. However, there was a great deal of uncertainty related to the results from the rolling window analysis, and the evidence should be viewed with caution
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