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‘Configuring an International Tax Framework for Emerging Commercial Exploitation of Space’
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Working thematically: changing the path to leadership for the third space
Get PDFWhat does leadership mean in the third space, and how is it changing? This opinion piece offers a perspective on third space leadership, through embracing thematic working and drawing together often disparate elements of the academy. The paper argues that the future workforce of HE depends on third space leadership and that the skills, attributes and opportunities, such as managing “supercomplexity” (Barnett, 2000) and “complex collaboration” (Veles et al, 2019) must be leveraged in order to support and encourage those who already work in this space. It offers two proposals that would effect the changes necessary to realise this, including looking at different HE contracts and criteria necessary for senior leadership
Decolonising the Higher Education Curriculum: Engaging with Liminality
Get PDF‘Decolonising the Curriculum’ (DtC) is now a well-established phrase in the vernacular of higher education institutions (HEIs). The recent movement can be traced back to the 2015 Rhodes Must Fall campaign at the University of Cape Town, South Africa, and the parallel campaign at the University of Oxford, United Kingdom (UK), where students rebuked the colonial legacies in Higher Education Institutions (HEIs) and called out the predominantly ‘White’ syllabi they were taught. In the 2014 film ‘Why is My Curriculum White?’ produced by University College London as part of a broader National Union of Students campaign, students expressed the many ways that their education was incomplete, with critical elements missing, omitted and excluded from their curriculum.1 It is important to note that colonialism has taken many forms over time, with many different impacts on higher education. Rizvi et al. (2006) highlight that understanding the legacies of colonialism helps overcome ahistoricity, recognising that identity and difference should not be reduced to essentialist terms or binary logics (see also Bhaba, 1994). Nevertheless, it is clear that students in these movements conveyed their frustration with the way in which monoculturalism was normalised and reproduced in their educational experiences. At the centre of these calls is a recognition that education is intrinsically linked with power, functioning both as a tool of empire and colonial thought, and therefore a critical space to expose and challenge the ongoing impact of colonialism. One of the key sites to expose and challenge the impact of colonialism, to initiate resistance and transformation, is the higher education curriculum
Flood Susceptibility for Storage Dams Locations to Reduce the Risk of Flash Floods and to Harvest Rainfall Utilizing a <scp>GIS</scp> Spatial Distribution Model and the Analytical Hierarchy Approach
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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.Flooding is a natural calamity that causes widespread devastation, including severe infrastructure destruction, significant economic consequences, and social disturbances around the world, particularly in the Sinai region. Wadi Ked is one of Sinai, Egypt's, most vulnerable districts to flood hazards, and it is the location used for this study. This study aims to create a map of flood‐prone areas in Wadi Ked by combining Geographic Information System (GIS) technology and multi‐criteria decision‐making (MCDM) techniques, utilizing the Analytical Hierarchy Process (AHP) methodology. To achieve the study's goal, flood‐related factors such as elevation, slope, distance to roads, distance from streams, annual rainfall, drainage density, topographic wetness index, land use and land cover, normalized difference vegetation index, soil type, and curvature were weighted and overlaid. The results show that 26.91% of the areas studied have a low sensitivity to flooding, whereas roughly 73.09% of the area is moderately to very highly vulnerable to flooding. The study proposed a dam with a height of 30 m, a width of 0.416 km, and a lake capacity of 31.74 million cubic meters (MCM). The surface runoff volumes from 50‐ and 100‐year storms in sub‐basins 1–5 are 23.07 MCM and 29.66 MCM, respectively. Model validation was performed by comparing susceptibility maps generated from literature‐based and expert‐based AHP weights, revealing a 98% spatial agreement and a Kappa coefficient of 0.995, confirming the model's robustness. This study offers value to decision‐makers and planners by utilizing morphometric properties and flash flood risk maps to identify suitable locations for dams.Brunel University Londo
Joint Attention-Guided Multitask Feature Sharing Network for High-Speed Train Fault Diagnosis
Get PDFIntelligent fault diagnosis of traction systems is vital for the reliability and safety of high-speed trains. Conventional methods extract features solely from fault signals to determine fault categories, neglecting the impact of operating conditions on traction systems. To address this limitation, multitask learning methods have been explored to simultaneously distinguish fault categories and operating conditions. However, due to the high cost of collecting high-speed train fault data, the available data are often extremely limited. Considering the parameter-intensive nature of multitask learning models and the scarcity of fault data, these models are prone to potential overfitting risks during the training process. In this work, we propose a novel joint attention-guided multitask feature sharing network (JA-MFSN) tailored for high-speed train traction system fault diagnosis. Our JA-MFSN integrates a novel joint attention module (JAM) that captures both task-shared and task-specific features with reduced parameter overhead, effectively mitigating overfitting risks. The network architecture balances model complexity and performance, enabling robust multitask learning under data-scarce conditions. Experimental results conducted on the hardware-in-the-loop (HIL) high-speed train traction control system simulation platform clearly demonstrate the superiority of the JA-MFSN approach over several existing methods.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62233012);
Jiangsu Provincial Scientific Research Center of Applied Mathematics (Grant Number: BK20233002);
Suzhou Science and Technology Programme (Grant Number: SYG202106);
10.13039/501100019054-Jiangsu Provincial Qinglan Project (Grant Number: 2021)
PID Containment Control for Multi-Agent Systems With Multi-Rate Measurements Under Sensor Resolution Constraints
Get PDFThis article investigates the proportional-integral-derivative (PID) containment control problem for a class of linear MAS with multirate measurements under the constraint of sensor resolution. The sensors of agents are classified into two distinct groups, characterized by their relatively fast and slow sampling periods. The concept of sensor resolution is introduced to quantify the ability of sensors to detect the smallest changes in information. A PID controller with an improved structure is proposed to achieve containment control, ensuring that follower agents remain within the convex hull formed by the leader agents. The closed-loop system is reformulated into a simplified representation, incorporating both sampling characteristics and communication topology. Sufficient conditions are then derived to guarantee the exponentially ultimate boundedness of the tracking error. Based on these conditions, an iterative algorithm is developed for computing the required controller gains. Finally, a simulation study, along with comparative analyses, is conducted to validate the effectiveness of the proposed approach.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61933007, 62273087 and U21A2019);
10.13039/501100013156-Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology (Grant Number: 1083142501018 and 1083142401006);
Hainan Province Science and Technology Special Fund (Grant Number: ZDYF2022SHFZ105);
10.13039/501100000288-Royal Society of the U.K.;
Alexander von Humboldt Foundation of Germany
A Review of AI-Enabled Personalised Teaching (2021–2025): Progress, Impact, and Future Directions
Get PDFBetween 2021 and 2025, AI-enabled teaching emerged as a key innovation in addressing global educational challenges such as teacher shortages, learning disparities, and skills gaps. For the first time, it promised to give learners outside of a lab or limited settings, a personal teacher available to support their diverse needs in highly personalised ways 24/7. This paper critically reviews the evolution of AI-integrated teaching, synthesising insights from existing literature alongside findings from four major research studies conducted by the authors during this period. Central to these investigations is OIAI, an AI-teacher system developed and piloted by the researchers across Africa, Europe, Asia, North America and South America. These form the basis of a pioneering implementation in two African nations; Kenya and São Tomé and Príncipe, in 2025
Bayesian monitoring of machining processes using non-intrusive sensing and on-machine comparator measurement
Get PDFMachining processes are largely reliant on manual intervention and non-value-added processes, such as post-process inspection, to achieve end-product conformance. However, the ever-increasing demand for high manufacturing productivity combined with low costs and high product quality requires online monitoring systems to provide real-time insights into the cutting process and minimize the volume of non-value-added processes. Most of the published work on machining process monitoring focuses on intrusive measurement equipment, such as dynamometers, to predict the dimensional quality of machined parts, preventing industrial exploitation due to practical limitations. The main focus of this work is to address this issue by developing a new product health monitoring method for machining processes using non-intrusive and low-cost instrumentation and data acquisition (DAQ) hardware. The sensing setup in this work includes an acoustic emission (AE) sensor and two accelerometers in the work holding. The proposed monitoring system is applied to milling experiments using Gaussian process regression (GPR) for probabilistic nonlinear in-process product condition monitoring. Validation results show the effectiveness of the GPR model to provide accurate probabilistic predictions of product health metric deviations with reasonable uncertainty estimates considering the large variability of the data. In addition, a Bayesian inference methodology is derived to dynamically incorporate subsequent information from on-machine probing (OMP) with a comparator method, improving the accuracy and robustness of the proposed solution. Specifically, it is demonstrated that a precision-weighted combination of prior information from the posterior predictive distribution for a future observation and new metrological information from on-machine comparator measurement (OMCM) can clearly improve posterior inferences about the end product condition.The author gratefully acknowledges the Royal Society for the grant RGS\R2\222098
Low visibility, low priority: Gambling and probation work in England and Wales
Get PDFProbation and gambling harms final report.This research was funded by the Bristol Hub for Gambling Harms Research through its Research Innovation Fund. The Bristol Hub for Gambling Harms Research is funded by a £4 million grant from the national charity GambleAware
Misrecognition and Responsibilisation in Extreme Events: Towards Recognition‐based Accountability in Academia
Get PDFSupporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/1467-8551.70032#support-information-section .This essay interrogates how extreme events including the COVID-19 pandemic, climate disasters, and political conflict, amplify structural inequalities in academia. Drawing on critical autoethnographic material from an Early Career Researcher with intersecting marginalisations, we show how crises expose and intensify two mutually reinforcing dynamics: misrecognition (institutional neglect of care responsibilities, political vulnerability, and embodied identity) and responsibilisation (the shifting of crisis management onto individuals). We demonstrate how these processes operate through institutional silence and performativity mechanisms that simultaneously erase vulnerability and demand uninterrupted performance, making individual adaptability appear both natural and necessary. By situating these lived experiences within Honneth's theory of recognition and Foucault's concept of responsibilisation, we theorise how their interaction deepens disadvantage for vulnerable groups during and after crises. In response, we propose Recognition-based Accountability (RbA) as a framework for institutional reform. RbA shifts the emphasis from individual resilience to structural responsibility, outlining actionable, care-oriented pathways for embedding equity and recognition into crisis governance in management education. This essay thus contributes to debates on academic inequality and the future of work by revealing the embodied costs of institutional neglect and offering a model for reorienting crisis response toward justice, care, and accountability
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