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On the use of UAV-thermal imaging for CFD validation of urban thermal microclimate
No full textComputational Fluid Dynamics (CFD) simulations are widely applied to assess urban microclimate processes and adaptation strategies. However, their accuracy and reliability critically depend on high-quality validation data. Although field measurements and reduced-scale wind-tunnel testing are commonly used for validation, the use of remote sensing methods remains limited despite their potential. This study systematically evaluates UAV-based thermal imaging as a tool for validating microscale CFD predictions of urban thermal conditions. The case study focuses on the city centre of Semarang, Indonesia, where ground-truth field measurements and UAV surveys with visible RGB and infrared (IR) imaging are conducted. CFD simulations are performed for the same area using 3D URANS with the realizable k–ε model on a high-resolution computational grid. Results show that (i) UAV-IR data and ground-truth measurements differed by 0.47 °C – 1.40 °C across asphalt, concrete, and soil–grass surfaces ranged from, confirming the accuracy of UAV thermal imaging; and (ii) CFD simulations deviated by 3.88 °C in surface-averaged temperatures for impervious-based areas compared with UAV-IR data. These findings highlight UAV thermal imaging as a practical and data-driven approach for validating CFD models, enabling more robust analyses and design of sustainable urban thermal environments
CFD simulations of running aerodynamics:Impact of computational parameters
No full textRunning is a fundamental discipline in athletics, yet its aerodynamic characteristics have not yet been intensively studied, particularly from a computational perspective. In recent years, Computational Fluid Dynamics (CFD) has become an increasingly valuable tool for advancing research in sports aerodynamics. However, the reliability of CFD predictions depends strongly on the selection of computational parameters which remains insufficiently explored in the context of human running. This paper presents a detailed study on the impact of grid resolution, computational domain size, and turbulence modelling on the computed drag area for a full-scale female runner manikin. The CFD simulations are validated by comparison with wind tunnel measurements performed in a geometrically matched test section. The sensitivity analysis provides practical guidelines for generating grids that balance accuracy and computational economy. The blockage ratio (BR) is found to be a critical parameter: values exceeding 3.5% result in drag overestimations larger than 2.8%. Among the turbulence models tested, transition-sensitive models (γ–SST and T–SST) in pseudo-transient RANS formulation and the hybrid scale-adaptive simulation (SAS) approach showed the best agreement with experimental results. Based on these findings, the study proposes a set of best-practice guidelines for reliable and cost-effective CFD simulations of running aerodynamics
R-RNet: Probability-Driven Networks for Pedestrian Trajectory Prediction
No full textAccurate prediction of pedestrian trajectories is crucial for safe motion planning of autonomous vehicles in urban environments. Many existing temporal and generative models are constrained by the long-tailed distribution of the data, which limits their ability to handle random or irregular pedestrian movements. Moreover, few studies have addressed the problem of scoring and probabilistic evaluation of predicted trajectories, despite their importance for downstream decision-making tasks. To address these issues, we propose a regularization-randomization network (R-RNet). The core regularization-randomization (R-R) module enables flexible trajectory prediction across diverse scenarios, while the probability predictor provides trajectory scoring and probability estimation to enhance reliability and utility in subsequent tasks. Besides, a self-attention mechanism is utilized to enhance prediction performance by capturing features from the distribution of the goals. The experimental results on the ETH and the UCY datasets show that R-RNet is capable of making reliable evaluations on output trajectories and achieves competitive results in terms of average displacement error and miss rate, while maintaining a lightweight architecture. Extensive experiments and analyses underscore the critical importance of both regularization and randomization operations
Behind the beer: An examination of ‘entrepreneurial’ motives for starting a craft brewery
No full textBrewing has experienced a considerable revival in recent years with the number of brewers in the UK being at its highest level since the 1930s (Cask Report, 2018). After decades of mergers and takeovers saw the emergence of a small number of global brewing conglomerates, many of the recently established breweries have spearheaded what has been referred to as a ‘craft beer revolution’. Typically, producing small batches of artisan brews and with small workforces, the output of craft brewers accounts for approximately 2.5% of all beer sales in the UK, but is the fastest growing sector of the drinks market. The growth of the industry mirrors that seen by artisan food producers and has led some to suggest an emerging preference for rejecting mass produced food and drink products.Despite recognition of the craft beer industry’s emergence, growth and cultural significance, almost nothing is known about the individuals who started these new breweries, nor what their motivations for doing so were. Drawing upon 30 in-depth, semi-structured interviews with owner-brewers of craft breweries from across Scotland, this chapter presents findings examining owners’ backgrounds and motivations for starting their brewery. The findings show a range of motivations and expectations amongst the group of owners and provide a useful basis for making practical recommendations of how other aspiring craft beer ‘entrepreneurs’ can be best supported by the industr
Emerging patents versus brain eating amoebae, Naegleria fowleri
No full textPrimary Amoebic Meningoencephalitis (PAM) is a severe and often fatal infection caused by the free-living amoebae Naegleria fowleri. This condition typically results from exposure to contaminated warm freshwater/inadequately treated recreational water/or ablution/nasal irrigation with contaminated water. The management of PAM is hindered by the absence of effective treatment coupled with challenges in early diagnosis. This review explores emerging patents that could be utilized for the treatment, diagnosis of PAM, as well as water treatment. Recent patents from the past five years, along with research and innovations are reviewed and categorized into therapeutic agents, water treatment technologies, and diagnostic methods. It is hoped that collaboration and awareness between pharmaceutical companies, water industries, and academic institutions is essential for advancing effective strategies against this severe central nervous system pathogen.</p
Perceptions and Experiences of the Menstrual Cycle amongst Elite Adult and Adolescent Football Players
No full textThe purpose of this study was to investigate players’ experiences and perceptions of the menstrual cycle (MC) and the perceived impact on performance. Female elite adult (n = 31, age 24.6 ± 5.1 years) and adolescent (n = 65, age 15.0 ± 1.1 years) players completed an online questionnaire consisting of quantitative and qualitative questions. MC symptoms were experienced by 90.1% naturally menstruating participants (86.9% adolescents and 93.6% adults (x2 = 1.53, df = 2, p = 0.47, n = 92)), and 78.3% adolescents perceived their MC impacts performance, compared to 96.4% adults (x2 = 4.54, df= 1, p = 0.033, n = 74). Physical symptoms, psychological symptoms, and energy levels were cited as key reasons for the MC negatively impacting performance. Challenges in communicating MC experiences were reported by 44.92% (n = 23) adolescents compared to 20.0% (n = 6) adults (x2 = 7.29, df = 2, p = 0.026, n = 82), with a perceived lack of knowledge, ability to relate and awkwardness cited as key reasons. Football players report wellbeing and performance impacts due to their MC, highlighting the need for individual understanding and support. Furthermore, understanding the experiences of adolescents enables the development of targeted support structures that equip them with tools to manage and communicate about their MC, and hopefully preventing issues as they become senior players
High-contrast random systems of PDEs: Homogenization and spectral theory
No full textWe develop a qualitative homogenization and spectral theory for elliptic systems of partial differential equations in divergence form with highly contrasting (i.e. non-uniformly elliptic) random coefficients. The focus of this paper is on the behavior of the spectrum as the heterogeneity parameter tends to zero; in particular, we show that in general one does not have Hausdorff convergence of spectra. The theoretical analysis is complemented by several explicit examples, showcasing the wider range of applications and physical effects of systems with random coefficients, when compared with systems with periodic coefficients or with scalar operators (both random and periodic)
A Supply-demand Evaluation Framework for Uncovering Age and Gender Inequities in Urban Green Space Cooling- A Case Study of Fuzhou
No full textRapid urbanization and intensified urban heat island effects have increased the need for effective, equitable cooling strategies. Urban green spaces (UGS), as nature-based solutions, provide critical cooling benefits that support thermal comfort and enhance urban resilience. However, disparities in cooling needs and access persist across gender and age, with vulnerable populations often facing unequal access to UGS resources. Despite growing attention to UGS equity, methods for quantifying demographic-specific mismatches between cooling supply and population demand remain underdeveloped. To address this gap, we developed a supply–demand evaluation framework to examine spatial equity and age- and gender-related environmental injustices in UGS cooling benefits in Fuzhou, China. The results show: 1) UGS cooling benefits supply and demand exhibit broadly similar spatial patterns across demographic groups but divergent patterns between the urban center and periphery. 2) Fuzhou’s main urban area faces pronounced supply–demand mismatches, with elderly and female populations more affected by uneven resource distribution. 3) Significant disparities (p < 0.001) exist across age and gender groups, with children and middle-aged adults experiencing greater mismatches, while men face more severe supply deficits. Although UGS spatially favors vulnerable groups, substantial inequities in cooling access remain. Notably, targeted planning and management strategies were proposed for urban and green space systems, tailored to different population groups and types of supply–demand mismatch. This study highlights the urgent need for age- and gender-responsive UGS planning and offers a transferable approach to reduce cooling inequalities, supporting more equitable and climate-resilient urban environments
3D crop reconstruction: A review of hyperspectral and multispectral approaches
No full textHyperspectral imaging (HSI) has emerged as a powerful tool for precision agriculture, enabling the non-destructive monitoring of crop biochemical and physiological traits. However, HSI alone lacks structural context, which limits its ability to accurately capture complex canopy architectures and organ-level traits. Integrating HSI with depth-sensing modalities such as Light Detection and Ranging (LiDAR), Red, Green, Blue, and Depth (RGB-D) cameras, and computational reconstruction technique such as photogrammetry enables the generation of three-dimensional hyperspectral point clouds, combining spectral richness with geometric fidelity. This multi-modal fusion enhances crop trait estimation, including biomass, leaf chlorophyll content, canopy height, leaf area, and stress indicators, while improving the robustness of phenotyping under occlusions, shadows, and varying illumination. Dimensionality reduction, feature selection, and machine learning approaches, including deep learning and explainable AI, are useful for handling high-dimensional hyperspectral data and extracting actionable agronomic insights. Moreover, the integration of thermal, radar, and Global Navigation Satellite System (GNSS) data further expands the capabilities of multi-modal sensing, enabling continuous, all-weather crop monitoring and accurate spatial referencing. Despite these advances, most studies to date focus on controlled environments, highlighting the need for field-based validation to ensure the reliability and scalability of HSI-depth fusion techniques. This review consolidates current knowledge on multi-modal hyperspectral and 3D crop reconstruction, highlighting methods, applications, and challenges, and outlines future directions for implementing high-throughput, real-time phenotyping and precision agriculture solutions
Mechanical response and design formulae of stainless steel sandwich blast walls for offshore structures under explosive loads
No full textAccidental explosions in offshore operations, though low in probability, can cause significant structural damage. To safeguard personnel, critical assets, and surrounding infrastructure, blast walls are installed on offshore platforms and FPSO units as passive protective systems. Due to their high stiffness-to-weight ratio and lower overall cost, sandwich panel structures (SPS) are proposed as a viable alternative to conventional thin-walled steel blast walls. Among various SPS types, metallic square-cored SPS are particularly notable for their relatively simple construction and durability in harsh environments. The single-degree-of-freedom (SDOF) method, recommended by the Fire and Blast Information Group (FABIG) for blast wall design, cannot account for localised structural failures, such as connection damage, buckling, or membrane effects. This study provides detailed guidelines for the numerical simulation of stainless steel SPS blast walls, discussing various modelling approaches. The finite element analysis results were validated against experimental data available in the literature. The maximum mid-span deflection, a crucial design parameter, was examined under 180 geometric configurations using rigorous simulations. An empirical formula was proposed to predict the normalised maximum deflection of the back face, based on dimensionless parameters, with satisfactory R² values achieved. This formulation offers a valuable tool for the preliminary design of square-cored SPS blast walls and lays the foundation for structural optimisation
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