157082 research outputs found
Sort by
On action rate admissibility criteria
No full textWe formulate new admissibility criteria for initial value problems motivated by the least action principle. These are applied to a two-dimensional Riemann initial value problem for the isentropic compressible Euler fluid flow. It is shown that the criterion prefers the 2-shock solution to solutions obtained by convex integration by Chiodaroli and Kreml or to the hybrid solutions recently constructed by Markfelder and Pellhammer
Marine Mammals in the Anthropocene: Developing a Systematic Evidence Base of Threats to Nineteen Species
No full textIntroductionMarine mammals have long been affected by human activities.AimsTo understand the state of knowledge regarding anthropogenic threats, we systematically mapped peer‐reviewed and grey literature on this topic for 19 marine mammal species found in the North Atlantic.MethodsSearches in 2022 and 2024 resulted in 3390 relevant documents for review. Relevant records were extracted from each document (n = 6964 records), and threats were grouped into 13 major classes (e.g., climate change, fisheries, acoustic disturbance).Results & DiscussionOf the 19 species, bottlenose dolphins had the most records (n = 1365), and of the threat classes, fisheries had the most records (n = 2124), with 59% being associated with mortality. Mapping the study locations highlighted how records were unevenly distributed across each IUCN‐defined species range. Furthermore, species of conservation concern (i.e., globally assessed by IUCN as ‘Endangered’) often received comparatively little study effort. We highlight the species and threats that have to date received limited attention and discuss the potential reasons for disparities in research effort.ConclusionIncreased efforts to understand and appropriately mitigate threats are critical, given the continued co‐existence of marine mammals and human threats in the ‘Anthropocene’
Estimating the impacts of the wind field size, wind speed, turbulence, and no-fly zones on unmanned aerial vehicle flights in urban areas
No full textSafety assurance for unmanned aerial vehicle (UAV) flights has become increasingly crucial for advancing urban low-altitude transportation networks. The complex wind environment generated by dense building layout and narrow streets poses significant challenges to low-altitude UAV flights. For efficient and economical transportation, UAVs must navigate these conditions by avoiding dangerous wind zones while minimizing flight distances. This study established an integrated framework combining Reynolds-averaged Navier–Stokes-based computational fluid dynamics simulations with multi-objective path planning algorithms for planning short and safe UAV flight paths in complex urban wind fields. We evaluate critical factors influencing urban wind fields, including study area dimensions, wind directions, flight altitudes, and grid resolutions of wind data extraction. Results reveal that wind direction impact depends critically on UAV exposure to the approaching wind (headwind, tailwind, or crosswind). Generally, flight paths at high altitudes (∼90 m) exhibit greater deviation from the original path compared to low altitudes (∼30 m) due to increased exposure to regions of strong wind and high turbulence intensity. Furthermore, flight paths optimized using wind data extracted at finer grid resolutions (4 m) are shorter than coarser resolutions (12 m). Flight path planning employs an A* algorithm optimized for three objectives: minimizing path length, avoiding hazardous wind speeds, and circumverting areas of high turbulence intensity. This framework was used to evaluate the impact of urban wind environments on flight paths. The findings offer crucial insight for designing reliable and sustainable systems required for future urban air mobility management
Combination theorems for Wise's power alternative
No full textWe show that Wise's power alternative is stable under certain group constructions, use this to prove the power alternative for new classes of groups and recover known results from a unified perspective. For groups acting on trees, we introduce a dynamical condition that allows us to deduce the power alternative for the group from the power alternative for its stabilisers of points. As an application, we reduce the power alternative for Artin groups to the power alternative for free-of-infinity Artin groups, under some conditions on their parabolic subgroups. We also introduce a uniform version of the power alternative and prove it, among other things, for a large family of two-dimensional Artin groups. As a corollary, we deduce that these Artin groups have uniform exponential growth. Finally, we prove that the power alternative is stable under taking relatively hyperbolic groups. We apply this to show that various examples, including all free-by groups and a natural subclass of hierarchically hyperbolic groups, satisfy the uniform power alternative
This is our rhythm: academic becoming and realignment in deaf space
No full textDeaf scholars have long worked at the margins of academic institutions not designed for them. Designated deaf academic spaces—where deaf ways of knowing, teaching, and communicating are centered—remain rare. This study explores what becomes possible when such a space exists, presenting Dr Deaf as a case study. Drawing on interviews with participants and teachers, we show how deaf epistemologies and pedagogies are enacted through cross-stage responsibility and academic becoming through re-alignment of deaf participants and teachers. We also identify a distinct deaf rhythm that emerges in this space. At the same time, we recognize that these practices are not experienced or valued equally by all participants and teachers: needs, priorities, and ways of engaging differ, and Dr Deaf’s approaches may not resonate for all. Yet its values offer a flexible framework for imagining and sustaining other deaf academic and broader educational spaces
Process modelling and analysis of ikaite production for atmospheric CO<sub>2</sub> removal through ocean alkalinity enhancement
No full textThe production of ikaite, a metastable calcium carbonate hydrate, offers a promising pathway for atmospheric CO2 removal through ocean alkalinity enhancement. This study explores the feasibility of ikaite production through a three-step process, involving calcite (CaCO3) dissolution under elevated CO2 pressure, CO2 degassing from the calcium carbonate rich solution, and subsequent crystallisation. Here, a mathematical model was developed and validated against experimental data, and the effect of key operational parameters was examined. The calcite loading/dosage, particle size and CO2 pressure for dissolution, seed loading and particle size for crystallisation, and degassing pressure as critical factors have significant impact on process efficiencies. Under optimal conditions, involving CO2 pressures of 2 bar for dissolution, 0.01 bar for degassing, and 0.001 bar for crystallisation, with seed loading of 5 kg/m³ and seed particle sizes of 3 μm, the process achieved steady state ikaite production of 1.64 kg/m³ from a calcite feed of 0.83 kg/m³. This investigation demonstrates the technical viability of ikaite production through CO2 pressure swing and informs its future development as a potential contributor to climate change mitigation
AI-Driven Enzyme Engineering: Emerging Models and Next-Generation Biotechnological Applications
No full textEnzyme engineering drives innovation in biotechnology, medicine, and industry, yet conventional approaches remain limited by labour-intensive workflows, high costs, and narrow sequence diversity. Artificial intelligence (AI) is revolutionising this field by enabling rapid, precise, and data-driven enzyme design. Machine learning and deep learning models such as AlphaFold2, RoseTTAFold, ProGen, and ESM-2 accurately predict enzyme structure, stability, and catalytic function, facilitating rational mutagenesis and optimisation. Generative models, including ProteinGAN and variational autoencoders, enable de novo sequence creation with customised activity, while reinforcement learning enhances mutation selection and functional prediction. Hybrid AI–experimental workflows combine predictive modelling with high-throughput screening, accelerating discovery and reducing experimental demand. These strategies have led to the development of synthetic “synzymes” capable of catalysing non-natural reactions, broadening applications in pharmaceuticals, biofuels, and environmental remediation. The integration of AI-based retrosynthesis and pathway modelling further advances metabolic and process optimisation. Together, these innovations signify a shift from empirical, trial-and-error methods to predictive, computationally guided design. The novelty of this work lies in presenting a unified synthesis of emerging AI methodologies that collectively define the next generation of enzyme engineering, enabling the creation of sustainable, efficient, and functionally versatile biocatalysts
Techno-Enviro-Economic Assessment of Long-Term Strategic Capacity Expansion for Dubai’s Clean Energy Future Using PLEXOS
No full textWith global energy systems shifting toward sustainable solutions, Dubai faces the challenge of meeting rising energy needs while minimizing environmental impacts. This study explores long-term (LT) strategic planning for Dubai’s power sector through a techno-environmental–economic lens. Using PLEXOS® modelling software (Version 9.20.0001) and official data from Dubai’s main utility provider, a comprehensive model examines medium- and LT energy pathways. The analysis identifies solar photovoltaic (PV) technology as central to achieving Dubai’s goal of 100% clean energy by 2050. It also highlights the need to cut emissions from natural gas (NG) infrastructure, targeting a goal of 14.5% retirement of NG energy generation capacities by the mid-century. Achieving zero-emission goals will require complementary technologies such as carbon capture (CC), nuclear energy, and energy storage as part of a broader decarbonization strategy. This study further assesses the economic effects of climate policy, showing that moderate carbon pricing could increase the Levelized Cost of Energy (LCOE) by an average of 6% across the forecast horizon. These findings offer valuable guidance for decision-makers and stakeholders, particularly the Dubai Electricity and Water Authority (DEWA), in advancing a carbon-neutral energy system. By 2050, Dubai’s total installed generation capacity is projected to reach 53.3 GW, reflecting the scale of transformation needed to meet its clean energy ambitions
Viso: Robust Underwater Visual-Inertial-Sonar SLAM with Photometric Rendering for Dense 3D Reconstruction
No full textVisual challenges in underwater environments significantly hinder the accuracy of vision-based localisation and the high-fidelity dense reconstruction. In this paper, we propose VISO, a robust underwater SLAM system that fuses a stereo camera, an inertial measurement unit (IMU), and a 3D sonar to achieve accurate 6-DoF localisation and enable efficient dense 3D reconstruction with high photometric fidelity. We introduce a coarse-to-fine online calibration approach for extrinsic parameters estimation between the 3D sonar and the camera. Additionally, a photometric rendering strategy is proposed for the 3D sonar point cloud to enrich the sonar map with visual information. Extensive experiments in a laboratory tank and an open lake demonstrate that VISO surpasses current state-of-the-art underwater and visual-based SLAM algorithms in terms of localisation robustness and accuracy, while also exhibiting real-time dense 3D reconstruction performance comparable to the offline dense mapping method
A Feasibility Study to Practically Implement a High-Performance Circularly Polarised Antenna Array for Point-to-Point Wireless Communication
No full textThis article presents the design, fabrication and experimental validation of a compact linear series-fed microstrip antenna array with dual circular polarisation (CP) capability. The proposed structure consists of a (Formula presented.) slotted circular patch array excited via four microstrip lines using a coplanar proximity coupling technique. Dual-CP operation is achieved through two miniaturised and distinct microstrip power divider networks, enabling the generation of either left-hand or right-hand CP based on the excitation port. To maximise gain and efficiency, the design reduces feedline branching and employs optimised slotted patch elements, resulting in low power loss and high radiation efficiency. The antenna achieves a realised peak gain of 19.4 dBic across 12.2–12.7 GHz and a 3-dB axial ratio bandwidth from 11.9 to 13.1 GHz. Simulation and measurement results demonstrate excellent agreement. Thanks to its compact size, wide bandwidth, dual-CP functionality and high gain, the proposed antenna offers a promising solution for point-to-point wireless communication systems. Compared to existing multi- and single-layer microstrip-based CP arrays, this work introduces a simplified feed structure and improved performance, demonstrating clear advancement in antenna array design.</p
Access Repository Dashboard
Do you manage Heriot Watt Pure? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!