34575 research outputs found
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Probabilistic approach for the prediction of flight processes with uncertainty quantification – Application to block time
No full textMachine learning models are increasingly being used to predict flight processes, such as the early estimation of the flight block time, that is, the gate-to-gate time (the time from leaving the departure airport until the arrival at their destination). These predictions support airline operations through early identification of possible disruptions. The performance of machine learning models tends to be described by metrics that represent their overall quality, not capturing the uncertainty of individual predictions. However, modelling and considering the uncertainties of individual processes is fundamental when integrating these models into decision support tools. This is particularly relevant in the air transport domain due to the non-linearities on delay propagation (for flights and passengers) and cost, as some events can trigger a sharp increase in these, e.g. with passengers missing their connections. This article presents a generic approach to describe the level of uncertainty of each prediction based on the combined use of two models. This methodology could be applied to many transport indicators and expert systems; in this article, the target variable used to illustrate the methodology is the block time of flights. The approach consists of the combination of two models: the first model produces a first estimation of the target value (with a regression); this estimation is then corrected by the outcome of a second model, which characterises (with a probabilistic classifier) the error of the first model for this estimation. The outcome of the combined models is a probabilistic distribution of the target indicator. The performance of the models generated in this manner is studied through parametric analysis and using three metrics: accuracy, uncertainty and prediction interval coverage probability (PICP). The VIKOR methodology is used to assist and streamline the decision-making process of the end user by filtering and ranking Pareto alternatives across various modelling parameters. This approach is compared with alternatives such as considering a Gaussian distribution of error for all estimations, quantile regression modelling and bootstrapping
Representing Violence Against Women: Asylum, Voice, and Testimony
No full textThis timely interdisciplinary volume brings academic research into dialogue with women who have experienced the asylum process, activists, and NGOs. It reveals the obstacles that women are confronted with during asylum processes, when relaying their testimonies that involve violence. Women’s voices are marginalized and often erased because of multiple barriers within refugee status determination procedures and asylum and refugee reception systems. Conditions need to change so that women can voice their testimonies and know that they will be listened to and heard, and that their voices and experiences will “count” within asylum processes and lead to effective protection. This book is a site of knowledge exchange between women survivors and activists, and policy makers. It contains first-hand accounts of the asylum processes by women survivors and activists and offers examples of how the arts and humanities might open up avenues of expression and testimony for women seeking asylum through practices of co-production, creating safe spaces of representation for women to talk about their lived experiences of violence and exile but also, and crucially, resistance and resilience
Trump’s new America and the question of fascism
No full textThe United States is undergoing a revolutionary transformation. In this article, we offer a novel and original early analysis of New America (Trump 2.0) as a contemporary political project on a protofascist trajectory. Our analysis contributes to scholarly understanding in multiple different ways. First, it grounds present American warnings about fascism in their specific historical tradition, showing how current alarm over Trump 2.0 continues, rather than departs from, long-standing American anti-fascist discourse. Second, it theorises fascism as revolutionary transformation, distinguishing it from both traditional conservatism and authoritarian populism, and further proposing a framework demonstrating how political projects may escalate towards fascism. This serves both as an analytical tool and as an early-warning system for identifying when democratic backsliding crosses certain critical thresholds. Finally, it provides an account of multiple mechanisms of ‘loyalty’ creation in Trump 2.0 that operate as an active process and are crucial to the project’s complete realisation
Preprint: Abdominal subcutaneous fat is a stronger predictor of cardiometabolic risk markers than visceral fat in young lean rural Indians
No full textBackground: Central obesity has been associated with cardiometabolic diseases. Unlike in the white Caucasians, the abdominal subcutaneous adiposity has been associated with higher cardiometabolic risk in Indians. There are few studies in young Indians. We investigated associations of MRI measured abdominal subcutaneous adipose tissue (aSAT) and visceral adipose tissue (VAT) with cardiometabolic risk markers in young lean rural Indian adults. Methods: We measured aSAT and VAT adiposity by MRI in young adult participants in the PMNS cohort [18yrs, n=590 (310 men)]. We used multiple regression analysis to investigate their associations with a range of cardiometabolic risk markers (glucose-insulin indices, blood pressure, lipids, and inflammatory markers). Results: In multiple regression models, aSAT was significantly positively associated with 120-min OGTT glucose, insulinogenic index, total cholesterol, triglycerides, leptin, total leukocyte count, CRP and systolic and diastolic blood pressure, and negatively with Matsuda index and adiponectin. aSAT associations were stronger than VAT for most outcomes. In women, aSAT was associated with all parameters except HDL-cholesterol, whereas in men the associations were similar to those observed in the combined analyses. Conclusion: In young Indians, aSAT is associated with insulin resistance, dyslipidaemia, and inflammation, unlike in Western populations. Utility of targeting aSAT to prevent cardiometabolic diseases needs to be further investigated
Enhancing Student Success, Connecting the Dots and Creating the Conditions for All our Students to Flourish in This Ever Changing and Complex World of Work: A Case Study
No full textForeword: Ten Years of Plurimus
No full textThis foreword situates Plurimus within a lineage of systems-based menswear design emerging from early 2000s online knowledge communities centred on the work of Massimo Osti. These decentralised forums operated as informal research archives, where garments were documented, materials analysed, and construction methods debated, generating a design culture grounded in process, material intelligence, and modular thinking. Fabio Cavina’s trajectory from this environment through earlier projects in garment dyeing and modular construction informs Plurimus’s rejection of seasonal fashion cycles in favour of numbered, limited-edition garment systems engineered for adaptability and long-term use. Produced in Italy to high technical standards, Plurimus garments prioritise function, continuity, and refinement through wear. The portfolio documents a decade of this approach, presenting the brand not as a sequence of collections but as an evolving design system structured around durability, precision, and the avoidance of obsolescence
The Fables of the Academic Zoo: De-Legitimizing Dominant Micro-Practices Through Storytelling and Caring.
No full textContemporary academia is like a zoo where academics, like caged animals, are confined by dominant micro-practices, creating an individualistic, competitive, and output-driven neoliberal ecosystem. Whilst Although prior research highlights these practices, little is known about how to dismantle them, and rewrite the academic script. In this article, we unveil how to collectively de-legitimize our dominant micro-practices, transcending traditional writing by telling the fables of the Academic Zoo and creating a radically imaginative theory. We foster a reflexive recognition of our dominant micro-practices, revealing their hidden logics, and challenging their illusion of inevitability. Through our fables and their associated morals, we construct a three-phased process model of recognition, disruption, and transformation—embedded in our conceptual foundation of narrative theory and the ethics-of-care—in which academics collectively weaken the legitimacy of dominant micro-practices and create opportunities for alternative ways of organizing. We call on academics to C.A.R.E—create awareness of our dominant narratives, alter the naturalized perception of these narratives through questioning and deconstruction, redistribute responsibility for disruptive counter-action, and establish and embed care-full alternatives— – supporting the creation of a more inclusive and humane academic ecosystem where “Together We Can Make a Difference”
TriFlow-ILE: A Triangulated Framework for Flow Detections in Immersive Learning – Pilot Validation with Creative Tasks
No full textFlow states represent optimal conditions for learning, however, measuring flow in immersive learning environments (ILEs) is challenging. Self-report measures interrupt the experience being assessed, while behavioural observa-tion cannot access internal states. This paper introduces TriFlow-ILE, a trian-gulated framework that integrates lightweight electroencephalography (EEG), behavioural observation, and brief micro self-reports to evaluate flow during authentic creative activity. In a within-subject pilot (n = 4), each participant completed two 30-minute mask-sculpting sessions—clay and VR. Participants wore 8-channel EEG cap while creating masks in both media, with continuous neurophysiological recording, dual-angle video capture, and post-session as-sessments on flow, immersion and cognitive workload. This pilot implementa-tion of the framework evaluates its feasibility, identifying strengths, limita-tions, and refinements needed for larger scale implementation. Main findings include successful EEG data capture during active VR use, identification of individual baseline calibration requirements, and validation of the three-source protocol for flow classification. The framework offers ILE researchers a repli-cable method for objective engagement monitoring without experience disrup-tion. The discussion includes implications for adapting learning systems, tech-nical challenges in combining EEG with VR hardware, and methodological lessons learned that inform the ongoing main study
