http://hdl.handle.net/1893/2670 This community contains the ePrints and eTheses produced by the Faculty's staff and students. Mon, 02 Nov 2026 03:00:00 GMT 2026-11-02T03:00:00Z http://hdl.handle.net/1893/38423 Title: Meteorological Drought Under Climate Variability in the Wadi Sly Basin, Algeria (1967–2022) Author(s): Achite, Mohammed; Terzi, Tolga Baris; Pandey, Kusum; Jehanzaib, Muhammad; Caloiero, Tommaso Abstract: Meteorological drought is a major natural hazard in semi-arid regions, where high climate variability and strong dependence on precipitation intensify pressure on water resources and socio-economic systems. This study examined the spatiotemporal characteristics of meteorological drought in the Wadi Sly basin (northwestern Algeria) over the period 1967–2022, using long-term monthly precipitation records from seven meteorological stations. The Standardized Precipitation Index (SPI) was calculated at multiple time scales (1-, 3-, 6-, 9-, and 12-month) to characterize drought onset, severity, persistence, and temporal variability. In addition, drought severity probability and frequency analyses were conducted to evaluate the likelihood and recurrence of different drought classes. The results indicate pronounced inter-annual and decadal variability in drought conditions, with severe and prolonged drought episodes occurring during the mid-1980s, early-to-mid-1990s, and late 2010s. During these periods, SPI values frequently fell below −2.0, signifying extreme drought conditions. Spatial analysis reveals strong basin-wide synchronicity of drought events, suggesting the influence of large-scale atmospheric drivers, although localized variations in drought intensity remain evident. Overall, near-normal conditions dominate the record (accounting for approximately 60–70% of observations), while moderately dry conditions occur more frequently than moderately wet conditions at several stations. Drought characteristics exhibit strong scale dependence, with short-term droughts prevailing at shorter SPI time scales, while longer time scales emphasize drought persistence and accumulation. Overall, the findings indicate an increasing prominence of long-duration drought conditions in recent decades, as evidenced by recurrent low SPI values at longer aggregation scales. Such conditions may pose heightened risks to groundwater recharge processes and long-term water resource availability. Despite the limitations inherent in precipitation-based indices, this study provides a robust statistical framework for drought characterization and contributes valuable insights for improved drought monitoring, early warning systems, and climate-resilient water resource management in semi-arid basins Sat, 14 Feb 2026 00:00:00 GMT http://hdl.handle.net/1893/38423 2026-02-14T00:00:00Z http://hdl.handle.net/1893/38420 Title: Explaining solutions for decision support via Partial Solutions Author(s): Catalano, Giancarlo Antonino Pasquale Ignazio Abstract: Optimisation problems arise across numerous domains, with metaheuristics being widely adopted due to their flexibility and ease of use. Although the metaheuristic framework is relatively simple, the search process is sufficiently complex that it is effectively a black box. Users are often forced to accept results at face value despite the risks of faulty implementations, non-determinism, and unintended biases. To address these limitations, this research introduces an explainability framework for metaheuristics by extracting human-interpretable insights from generated solutions. Central to the proposed methodology is the novel concept of Partial Solutions—defined and implemented as part of this work—which represent understandable sub-structures within metaheuristic solutions associated with high fitness. To find these patterns, we use a multi-objective search method that leverages information relating to their complexity, fitness, and structure. The resulting patterns offer trade-offs between objectives, and each can be post-processed into an explanation. To quantify the “structure” of Partial Solutions, we developed two novel linkage learning methods and a new linkage evaluation procedure, which offers a superior trade-off between accuracy and execution time compared with existing methods. The utility and domain-agnostic nature of this framework are demonstrated and evaluated across several distinct applications. First, the methodology was applied to a complex industrial optimisation problem posed by British Telecom (BT), yielding insightful explanations. Second, the framework was adapted for a recommender system model, successfully generating explanations that satisfy stakeholder objectives. Furthermore, the same underlying methodology was utilised to construct transparent models for predicting solution fitness. To conclude, Partial Solutions are a flexible tool for explainability. They are shown to recover known patterns within benchmark problems, and to be applicable and insightful in large and complex problems such as British Telecom’s Staff Rostering. Our methodology can also be used beyond metaheuristics; for example, we apply it to a recommender system to produce domain-specific explanations. Finally, Partial Solutions can be used to predict fitness: we show that decision trees based on Partial Solutions are competitive with traditional approaches. We conclude the thesis with reflections on whether our objectives have been achieved, and possible future work. Partial Solutions may be used to implement efficient and more understandable metaheuristics, and the applicability of the explanations produced may be expanded beyond combinatorial optimisation. Mon, 15 Jun 2026 00:00:00 GMT http://hdl.handle.net/1893/38420 2026-06-15T00:00:00Z http://hdl.handle.net/1893/38414 Title: Plasticity in a bacterial global regulatory switch that drives a shift in antibiotic resistance and virulence Author(s): Correia, Annapaula; Manners, Emma J; Evans, Benjamin A; Malone, Jacob G; O’Grady, Justin; Mavrogiorgou, Eleni; Arminu, Sergio; Usai, Manuela; Naik, Dixita; McMillan, Stuart; Kay, Gemma L; Hill, Claire; Sudhakar, Padhmanand; Meader, Emma; Desbois, Andrew P Abstract: Antibiotic resistance and expression of virulence factors impact the outcome of infection by Pseudomonas aeruginosa. Pathogenesis is often modelled using the PAO1 reference strain but laboratory lineages vary in the sequence and activity of MexT, a global regulator impacting virulence, biofilm formation, and ciprofloxacin resistance. We defined the impact of active versus inactive MexT in PAO1 and observed transcriptomic changes affecting the expression of ~900 genes. Phenotyping revealed altered metabolism, antibiotic resistance, and virulence, resulting in striking variation across a ‘single’ model organism. We propose that antibiotic resistance promotes plasticity in mexT accounting for variation across lineages. We introduced antibiotic resistance into clinical P. aeruginosa isolates and observed mutations in mexT when selective pressure was removed, supporting the proposed evolutionary pathway. Overall, we have demonstrated the transcriptomic basis of MexT as a phenotypic switch in PAO1 and implicated antibiotic resistance as a cause of changes in mexT. Furthermore, MexS/MexT-regulated efflux is implicated in the antibiotic stress response and virulence, helping identify the mechanisms for rapid phenotypic switching through mexT and confirming that PAO1 is unlike most isolates. Improved understanding of the regulatory changes linked to antibiotic resistance is particularly relevant to P. aeruginosa where cycles of antibiotic treatment are common. Thu, 08 Jan 2026 00:00:00 GMT http://hdl.handle.net/1893/38414 2026-01-08T00:00:00Z http://hdl.handle.net/1893/38412 Title: Revealing potential Atlantic salmon bycatch hotspots from pelagic fisheries landings across the Northeast Atlantic Author(s): Borland, Aislinn; Elliott, Sophie; Gillson, Jonathan P; Utne, Kjell; Banas, Neil; Toms, Simon; Tyldesley, Emma; Bárðarson, Hlynur; Bull, Colin Abstract: Atlantic salmon (Salmo salar) marine survival has declined markedly over the past five decades, leading to concerns about future population viability. While many studies have explored the impacts of stressors such as climate change and predation, less is known about bycatch from pelagic fisheries targeting finfish species. This study, focused on the first few months of the salmon marine migration period, narrows down the space-time domains where pelagic fisheries bycatch is most likely to occur. Landings from an International Council for the Exploration of the Sea led data call were used to assess bycatch exposure. Temporal patterns of monthly landings of six commercially important pelagic finfish species (mackerel Scomber scombrus, herring Clupea harengus, horse mackerel Trachurus trachurus, sardine Sardina pilchardus, capelin Mallotus villosus, and chub mackerel Scomber colias) within the Northeast Atlantic region from 2000 to 2022 were considered alongside reconstructed salmon migration regions. This study indicated that bycatch exposure from herring and mackerel fisheries was higher than that of other pelagic fisheries along the shared salmon migration corridor between April and August, with cumulative exposure highest over time for the herring fishery. Southern salmon populations were also exposed to the horse mackerel and sardine fisheries in April. Temporal patterns of monthly pelagic landings were compared with patterns of marine return rates in salmon index populations, but no consistent relationships were present. Quantifying salmon bycatch rates at sea remains challenging due to highly variable and sparse data but, given the severity of declines across their range, conservation measures that address factors affecting marine survival of salmon are urgently needed. Future investigations using emerging technology in the pelagic fisheries identified in this study could provide opportunities to develop more robust information on bycatch risk to Atlantic salmon stocks and to direct appropriate mitigation measures. Thu, 15 Oct 2026 00:00:00 GMT http://hdl.handle.net/1893/38412 2026-10-15T00:00:00Z