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Optimization models for cumulative prospect theory under incomplete preference information
No full textProspect stochastic dominance conditions can be used to compare pairs of uncertain decision alternatives when the decision makers' choice behavior is characterized by cumulative prospect theory, but their preferences are not precisely specified. This paper extends the use of prospect stochastic dominance conditions to decision settings in which the use of pairwise comparisons is not possible due to large or possibly infinite number of decision alternatives (e.g., financial portfolio optimization). In particular, we first establish equivalence results between these conditions and the existence of solutions to a specific system of linear inequalities. We then utilize these results to develop stochastic optimization models whose feasible solutions are guaranteed to dominate a pre-specified benchmark distribution. These models can be used to identify if there exists a decision alternative within a set that is preferred to a given benchmark by all decision makers with an S-shaped value function and a pair of inverse S-shaped probability weighting functions. Thus, the models offer a flexible tool to analyze choice behavior in decision settings that can be modeled as optimization problems. We demonstrate the use of the developed models with two empirical applications in financial portfolio diversification and procurement optimization
Integrating geometric and causation probability approaches into Dynamic Bayesian Networks for real-time collision risk prediction
No full textMaritime transportation is vital for international trade, yet collision accidents continue to pose serious risks to navigational safety and global economic stability. This study develops a novel collision risk prediction model based on Dynamic Bayesian Networks (DBN), incorporating both geometric and causation probability approaches to realise real-time ship collision risk prediction and probabilistic risk assessment. Leveraging raw Automatic Identification System (AIS) data, the proposed model dynamically updates the probabilities of influential factors using Markov-chain-based transition analyses, mitigating uncertainties caused by noisy or incomplete data. In contrast to traditional deterministic models, the DBN captures mutual dependencies among dynamic risk factors, including variations in speed ratio, relative bearing, and temporal-spatial parameters such as Distance to Closest Point of Approach (DCPA), Time to Closest Point of Approach (TCPA) and relative distance. The model categorises collision risk into five discrete levels, ranging from very low to very high, providing decision-makers with actionable insights for real-time navigational safety. A key innovation lies in modelling these interdependencies among influential factors, which enables a holistic understanding of collision dynamics. Simulation results demonstrate that the DBN model outperforms traditional Collision Risk Index (CRI) approaches, particularly in accurately predicting complex collision scenarios and reflecting aggressive manoeuvres. This study presents a robust framework for maritime collision risk prediction, offering a foundation for enhancing navigational safety in increasingly congested and mixed-traffic environments involving the coexistence of manned and unmanned vessels.</p
A refinement of macroeconomy-housing price equilibrium: walking down long memory lane
No full textHousing prices are known to respond slowly and heterogeneously to macroeconomic variations from the demand and supply sides of housing. This offers a possibility to model the long-memory and varied persistence of housing price adjustments, through which a refined characterisation of the macroeconomic-housing price interaction in equilibrium can be developed. Our paper advances a theoretical argument, supported by empirical findings in the US, that macroeconomic variations trigger varied reactions on housing demand and supply sides. This leads to distinct trajectories of equilibrium housing price formations governed by differential price adjustments on the two sides of housing. An established longer memory on the supply side of housing demonstrates its higher persistence of disequilibrium deviations than on the demand side. In the equilibrium, certain macroeconomic factors are found to exert dual but heterogeneous roles in housing demand- and supply-side dynamics. The net role of each such factor is negative led by its even stronger negative role on the demand side compared against a smaller positive one on the supply side. Our findings contribute to deeper reflections on the likely ineffectiveness of macroeconomic interventions in housing price dynamics
Trade-offs for a resilient broiler sector: TRI-SoMe Chicken Stakeholder Workshop report, Birmingham, October 2025
No full textDoubling the diagnostic rate of at-risk metabolic dysfunction-associated steatohepatitis – leave no one behind’: authors reply
No full textFatigue risk management in healthcare: A scoping literature review
No full textBackground: Occupational fatigue among healthcare professionals is a complex, multifaceted issue associated with increased likelihood of medical error, compromised patient safety and negative impacts on staff mental and physical health. While safety-critical sectors such as aviation and rail have implemented formal systems to manage fatigue-related risks, it remains unclear whether similarly structured approaches exist or operate effectively within healthcare.Objective: This scoping literature review aimed to examine the current state of knowledge regarding fatigue risk management strategies and countermeasures in healthcare and explore the barriers and facilitators to their implementation. This review sought to highlight gaps and provide insights into advancing fatigue risk management practices within the healthcare context. Methods: A systematic literature search to June 2025 was conducted across Medline, CINAHL Ultimate, and Scopus databases. Search terms were developed based on key concepts related to healthcare professions and fatigue risk management. Studies were included if they examined fatigue risk management strategies, countermeasures or organisational perceptions of fatigue in healthcare.Results: Thirty-two studies met the inclusion criteria, including quantitative (n = 18), qualitative (n = 9), and mixed-methods (n = 5) designs. Findings were grouped into conceptual categories based on the study focus and/or intervention type. The majority of studies (n = 18) evaluated isolated interventions including informal/individual fatigue management strategies, napping, use of biomathematical models to predict fatigue risk, fatigue education, and the impact of scheduling practices. Only two studies reported on comprehensive, multi-component programmes. Nine studies explored staff perceptions and attitudes toward fatigue-related strategies, and three examined broader organisational understanding or design principles related to fatigue management. Key barriers to implementation included normalised cultural attitudes towards fatigue, limited managerial support, and inadequate infrastructure. Facilitators included improved staffing levels, better workload distribution, supportive leadership, and the development of non-punitive safety cultures that encouraged fatigue reporting.Conclusions: Despite growing awareness of the risks associated with occupational fatigue, healthcare systems continue to rely on fragmented, informal, and largely individual approaches to fatigue management. In contrast to other high-risk industries, healthcare has yet to embed fatigue management within formal safety governance structures. Advancing practice in this area requires a shift toward system-level thinking that is supported by organisational leadership, effective fatigue monitoring, and workforce education. Additionally, this shift also demands a cultural reorientation that recognises fatigue as a predictable and manageable safety risk that necessitates organisational accountability rather than individual resilience to prioritise both staff wellbeing and patient safety.<br/
Shaping metasurfaces: spatially varying origami architecture for programmable shape-morphing curvatures
No full textTwo inertial projection-type methods for solving pseudo-monotone variational inequalities with application to image deblurring problem
No full textOur purpose is to propose two different type of inertial algorithms for approximating a solution of pseudo-monotone variational inequality problem in the framework of Banach spaces. The proposed algorithms are established by using Mann’s iterative method and single projection type method with adaptive step-size. Strong convergence theorems for minimum-norm solution of the variational inequality problem are established without the prior knowledge of the Lipschitz constant of the mapping. Finally, some numerical experiments are performed to illustrate the advantage of the proposed methods and numerical experiments in image recovery are also presented. Our results generalize and improve some known results existing in the current literature.</p
Newly defined clinical obesity versus BMI-defined obesity: differential risks of overall death and adverse events in a population-based cohort
No full textAims: to compare the prognostic implications of the newly proposed clinical obesity classification against traditional body mass index (BMI)-defined obesity in a population-based cohort.Materials and Methods: using UK Biobank, we compared the impact of newly defined obesity, including clinical obesity (obesity status with obesity-related comorbidities) and pre-clinical obesity (obesity status with preserved organ function), with traditional BMI-defined obesity on death, cardiovascular disease (CVD), chronic kidney disease (CKD), and liver-related events (LREs). To further delineate heterogeneity within the clinical obesity group, we performed stratified analyses based on comorbidity burden (number of comorbidities), severity of adiposity, and presence of diabetes or hypertension.Results: a total of 502 129 participants were enrolled. About 375 585 (74.8%) had non-obesity, 126 544 (25.2%) had BMI-defined obesity (including 93 410 [73.8%] with clinical obesity and 13 875 [11.0%] with pre-clinical obesity). During a median follow-up of 15.8 years, clinical obesity was associated with significantly higher risks of death (HR = 1.097, 95% CI: 1.071–1.125, p < 0.001), LRE (HR = 1.103, 95% CI: 1.040–1.169, p < 0.001), CVD (HR = 1.118, 95% CI: 1.091–1.146, p < 0.001), and CKD (HR = 1.111, 95% CI: 1.081–1.141, p < 0.001) compared to BMI-based obesity. Conversely, pre-clinical obesity showed significantly lower risks across these outcomes. High-risk clinical obesity subgroups with multiple comorbidities or severe adiposity showed particularly increased risks.Conclusion: the clinical obesity classification helps to define a high-risk phenotype with substantially increased risks of mortality and major comorbidities, while pre-clinical obesity defines a distinct subgroup with more favourable outcomes
Navigating the noise: exploring black hole systems using time-series analysis
No full textUnderstanding variability in accreting systems offers one of the most powerful tools for probing the innermost regions of compact objects — regions otherwise inaccessible to direct imaging. Variable signals encode information about everything from the geometry to the dynamics of the innermost flows. Time-domain astrophysics comes with immense potential, but it also brings many challenges. In this thesis, I aim to show the possibilities of time domain studies in equal measure to their caveats and pitfalls. I will demonstrate traditional techniques in the Fourier domain to brand new machine learning routines. Then I will show how no technique in this field is obsolete; they all build upon each other. This work focuses on publicly available survey data, illustrating the immense potential of what we already have and preparing us for what is to come. In a world where data is coming so fast, we might need to ask, can we keep up
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