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Consensus and Divergence in Explainable AI (XAI): Evaluating Global Feature-Ranking Consistency with Empirical Evidence from Solar Energy Forecasting
No full textopen access articleThe growing reliance on solar energy necessitates robust and interpretable forecasting models for stable grid management. Current research frequently employs Explainable AI (XAI) to glean insights from complex black-box models, yet the reliability and consistency of these explanations remain largely unvalidated. Inconsistent feature attributions can mislead grid operators by incorrectly identifying the dominant drivers of solar generation, thereby affecting operational planning, reserve allocation, and trust in AI-assisted decision-making. This study addresses this critical gap by conducting a systematic statistical evaluation of feature rankings generated by multiple XAI methods, including model-agnostic (SHAP, PDP, PFI, ALE) and model-specific (Split- and Gain-based) techniques, within a time-series regression context. Using a LightGBM model for one-day-ahead solar power forecasting across four sites in Calgary, Canada, we evaluate consensus and divergence using the Friedman test, Kendall’s W, and Spearman’s rank correlation. To ensure the generalizability of our findings, we further validate the results using a CatBoost model. Our results show a strong overall agreement across methods (Kendall’s W: 0.90–0.94), with no statistically significant difference in ranking (p > 0.05). However, pairwise analysis reveals that the “Split” method frequently diverges from other techniques, exhibiting lower correlation scores. These findings suggest that while XAI consensus is high, relying on a single method—particularly the split count—poses risks. We recommend employing multi-method XAI and using agreement as an explicit diagnostic to ensure transparent and reliable solar energy predictions
Synthetic Residential Building Energy-Consumption Dataset Generation Through Parametric Simulation for Hot–Arid Egypt
No full textopen access articleBuildings account for a substantial share of global energy demand, and decisions made during conceptual design strongly influence long-term operational consumption. This study presents an open, simulation-derived dataset to support early-stage estimation of residential energy use in a hot–arid context (New Cairo, Egypt). A parametric Rhino/Grasshopper Workflow coupled with EnergyPlus was used to generate 12,000 annual simulations. The simulations were produced by systematically sampling key geometric, envelope, glazing, and operational variables, including building dimensions, orientation, window-to-wall ratio, envelope construction options, glazing properties, internal loads (lighting and equipment), and thermostat setpoints. For each case, annual end-use outputs (heating, cooling, lighting, and equipment energy) are reported alongside the corresponding input features, enabling design-space exploration, sensitivity analysis, and the development of surrogate and machine-learning models for rapid decision support. Verification checks and plausibility screening were applied to confirm successful simulation execution and consistent data extraction. In addition, dataset-level sampling diagnostics (marginal balance and correlation screening) are reported to support robust reuse in surrogate and machine learning studies. The resulting dataset and documentation provide a reusable resource for researchers and practitioners investigating energy-informed residential design under hot-climate boundary conditions
Formalization of MEV: Modeling, Security Requirements, and Mitigation Strategies
No full textopen access articleMaximal Extractable Value (MEV) threatens the fairness and decentralization of blockchain systems. It arises when entities controlling transaction ordering such as miners, validators, and builders exploit that position for financial gain, unbalancing incentives and undermining impartial execution. Despite prior work, the field remains fragmented: definitions conflict, terminology overlaps, and many studies focus on narrow behaviours while overlooking dynamics across roles and protocol layers. This paper formalises MEV as a role dependent optimisation problem that unifies attacker strategies, security requirements, and mitigation mechanisms within a single framework. We model adversarial behaviours including front-running, back-running, sandwiching, and suppression attacks and express MEV extraction as a constrained optimisation defined by actor roles, information asymmetries, and timing assumptions. On this foundation, we introduce a taxonomy of mitigation approaches covering proposer–builder separation (PBS) architectures, threshold-encryption and Verifiable Delay Function (VDF) schemes, mempool-secrecy techniques, priority gas auctions (PGAs) and auction-based mechanisms, machine-learning detection frameworks, and Layer 2 rollup sequencing designs. This view enables comparison of trade-offs in decentralisation, verifiability, latency, and trust assumptions. To demonstrate applicability, we analyse three samples, BEAST-MEV, SUAVE, and MEV-Boost, used as case studies of confidentiality, hybrid coordination, and economic separation. These examples show how mitigation philosophies can be compared through the model, revealing strengths, dependencies, and performance implications. The framework introduces metrics for sequencing fairness and mitigation effectiveness, unifies Proposer Extractable Value (PEV) and Builder Extractable Value (BEV) within a single model, and connects formalism to deployable protocol designs. The paper concludes by outlining challenges, including cross-domain MEV and shared sequencer dynamics
ACCELERATING UKRAINE'S RECOVERY: A Formal Response from De Montfort University's Research Community to the Royal Society Conference on Ukraine's Recovery, May 15 - 16, 2023
No full textThe DMU Policy Unit has produced this report in response to the 2023 Royal Society conference on “Ukraine’s recovery: rebuilding with research”. We have been closely following the developments in Ukraine, and our teams are determined to contribute our time and expertise to support the nation's resilience and reconstruction efforts. We firmly believe that Ukraine can build long-term resilience and prosperity by strengthening its efficiency, business performance, economic growth, and civil society. As such, DMU is committed to supporting Ukraine's recovery and reconstruction efforts by leveraging our expertise in digital technology and addressing gaps in technology usage and development. We recognise the critical role of digital innovations in expanding the capacity of the Ukrainian government to manage emerging challenges, enhance communication, and streamline processes with reduced bureaucracy. We also believe that particular attention should be given to how Ukraine can modularise its approaches to adapt to the current situation, such as implementing dispersed and decentralised energy systems and agriculture, while empowering domain specialists in these fields. Furthermore, protection of sensitive information and safeguarding the public from misinformation and propaganda during this critical time of war is a key parameter for this success. As such, DMU can provide valuable assistance in mitigating the risks associated with deepfakes and ensuring effective data management and protection that aligns with EU requirements. Our report also emphasises the significance of building confidence in actors on the ground, encouraging private development and voluntary initiatives as the driving forces behind Ukraine's victory (building on successful initiatives like the “People's Project”). We believe that by fostering a culture of innovation, where individuals are not afraid to try, make errors, and try again, Ukraine can unlock its true potential and become a global hub for technology, entrepreneurship, sustainable energy, and agriculture. Knowledge transfer and capacity building are at the core of our approach. DMU is committed to facilitating knowledge transfer to Ukraine in technology, as well as shaping skill assessment systems, and establishing partnerships with Ukrainian universities and think tanks. Our existing partnership with the West Ukraine National University serves as a strong foundation for expanding our collaborations and building memoranda of understanding with other institutions. Through this, we hope to identify potential partners and areas of work, build comprehensive data infrastructure, and expand research capacity to aid Ukrainian research institutions in becoming research self-sufficient and tackle emerging challenges independently. To effectively respond to the Royal Society conference report, we formed a coalition of 58 researchers from all three DMU faculties, each contributing to a specific area of expertise. The report is structured around seven key themes, each addressed by a dedicated team of experts. These themes encompass a wide range of areas, including digital technologies, health and well-being, sustainable development, labour and enterprise, institutional reform, international strategy, and higher education development. The report highlights relevant expertise at DMU that speaks to the main messages of the Ukraine Recovery conference in May 2023. It highlights innovative research projects and novel approaches across various disciplines, each carefully selected to address the challenges and priorities identified during the conference. We thus aim to leverage our interdisciplinary expertise and successful collaborations to provide insights that can contribute to the efficiency and effectiveness of the recovery process. As such, we invite all stakeholders involved in this project to explore the wealth of expertise and innovative ideas that DMU has to offer. We are confident that the collective expertise and dedication of DMU’s research community, combined with the leadership of the Royal Society and its partners, can make a significant impact on Ukraine's recovery journey. We stand ready to work hand in hand with the Ukrainian government, the UK Science and Technology Network, and the Universities Policy Engagement Network to transform our recommendations into tangible actions that will contribute to Ukraine's long-term resilience and success
Failure analysis of retrieved stainless steel Exeter hip implants: A fractographic and corrosion perspective
No full textopen access articleIn this study, three fractured stainless steel Exeter (REX 734) hip joint implants were analyzed to identify the underlying failure mechanisms. These cemented hip stems with a polished surface finish failed earlier than their expected service life, indicated by sudden pain in the patients, necessitating revision surgeries. Optical and scanning electron microscopy were used to analyze the explanted hip stem fracture surfaces. The fractograms exhibited three distinctive zones; (1) crack initiation at the anterolateral part of the stem, (2) crack propagation zone with beach marks and striations, and (3) final fracture zone. Fatigue was the dominant failure mechanism. The anterolateral surface of the implants close to the fracture initiation site showed discoloration and surface alteration, possibly due to corrosion, and the presence of extrusions and intrusions formed by slip band accumulation, causing stress concentration and crack initiation. Also, elongated and sharp-edged phases enriched in niobium were found at the crack initiation site and throughout the microstructure. Medical radiographs indicated a lack of cement fixation at the proximal part of the stems, causing implant instability and ingress of body fluids, which potentially led to corrosion reactions. The crack propagation zone decreased in relative size with higher patient weight and BMI. Overall, this study suggests the possibility of corrosion contributions and a role of niobium-rich precipitates in the crack initiation and fatigue failur
Cripping multispecies care: Explorations of disability, abelism and speciesism in multispecies homes
No full textopen access article
This project was funded by a Canadian research council and led by the University of Guelph (Department of Applied Nutrition and Family Studies). The research groups and centres involved were the FIDO Research lab which focuses on dog-human relationalities and The Re•Vision Centre for Art and Social Justice, an arts methodology research hub at the University of Guelph.Increasingly intersecting work in disability and animal studies reveals the interconnection of oppressive hierarchies and how these operate within and across species. This article extends such dialogues into the home, considering the ways that disability, ableism, and speciesism show up in multispecies care. Pulling from thematic analysis of twenty semi-structured interviews exploring dog-human caregiving practices, we argue that humans make sense of their care relationships with dogs in ways which both reinforce and “muddy” ableist logics within the home. We explore six themes: (1) intimate care work and disabled animal companions; (2) breeds and capital; (3) pathologization of “problem” dog behaviour; (4) animal care work and disabled human companions; (5) trauma and recovery in and across species; and (6) intelligence and madness in interspecies relationships. Overall, mobile and place-based interviews with twenty participants on caregiving in multispecies homes reveal language and discourses that reproduce ableist and anthropocentric understandings of, and relationships with, animals, alongside transgressive relationalities grounded in reciprocity, vulnerability, and care
'Crazy Dog Moms'? Gendering relational dynamics, carework and pet parenting practices in multispecies Canadian homes
No full textopen access article
This article is from a project funded by a Canadian research council and led by the University of Guelph, Canada and colleagues in the Department of Family Relations and Applied Nutrition. Research groups involved were the FIDO lab, which focuses on human-animal connection, with an emphasis on kin networks which include both dogs and humans and The ReVision Centre for Art and Social Justice, an arts methodology research hub at the University of Guelph.Social scientists have begun to consider the importance of interspecies relationalities in homes, yet, the field of family studies has largely overlooked conceptualisations of families as multispecies. This paper contributes to research contesting this anthropocentrism by recognizing animal companions as family members implicated within domestic relationships. Drawing on the findings of twenty mobile and placed-based interviews and nine digital/multimedia stories, we explore caregiving in multispecies Canadian homes, with a focus on gendered dynamics and parental parallels within relationships. Gendered dynamics identified as themes in our dataset entailed: dogs as protectors of women, women driving dog acquisition, women’s closer relationships with dogs, and gendered companion animal care labour. Participants adopted parental discourses prominently by self-identifying as mothers or fathers to their dogs, referring to dogs as their babies, discussing divergent parental roles within households, dogs’ significance to empty nesters, and dogs as replacement or practice children. Our findings illustrate the ways men and women engage in canine carework differently and unevenly and display divergent gendered performances of canine companionship. We contribute to growing work at the intersection of family and animal studies which explores multispecies households and care labour, positioning companion animals within kin networks and challenging dominant humancentric research paradigms
From Their Own Voices: The Lived Experiences of Women on Corporate Boards in Nigeria
No full textPurpose
Drawing on social categorisation and institutional theories, this research seeks to examine the challenges faced by female board members in Nigeria, prior to and during their tenures, and to elucidate the strategies they employ to overcome these obstacles.
Design/Methodology/Approach
This study utilises a qualitative methodology, conducting focus group discussions and semi-structured interviews with 22 female board members from various Nigerian corporations. This approach enables an in-depth exploration of their experiences, allowing for the identification of key challenges and strategies for overcoming barriers to board participation and leadership in a weak institutional context.
Findings
We identify key impediments at the organisational, socio-cultural, and individual levels that obstruct women's access to and participation on corporate boards. Additionally, we explore how these women navigate and interpret these challenges, providing valuable insights into their experiences. Our analysis culminates in the proposal of strategic actions, as well as firm- and policy-level recommendations, aimed at enhancing opportunities for female board members and promoting improved corporate governance within the Nigerian context.
Originality/Value
This study offers a nuanced understanding of the multifaceted barriers to female board representation, examining both organisational and socio-cultural challenges as well as individual challenges. By providing practical insights, it aims to advance gender diversity in corporate leadership, particularly within developing economies, highlighting actionable strategies and policy recommendations to enhance the inclusion and effectiveness of female board members
Redistribution, growth, and inequality: Insights from experimental dynamic public good games
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper investigates the interplay between income inequality, growth, and redistribution in a dynamic public good game. Redistribution, as expected, leads to lower inequality but it does not necessarily reduce growth. Especially in settings characterized by high initial inequality, a high tax rate can produce similar wealth levels as without taxation while reducing inequality. On average, we find that people tend to favor more redistribution over time, but there is substantial heterogeneity in this trend. We also find that individuals who are more favourable to redistribution contribute more to the public good
Triple-A Supply Chains: The Bridge Between Supply Chain Analytics and Supply Chain Resilience
No full textThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This study explores the critical interplay between supply chain analytics (SCA), the Triple-A supply chain framework (agility, adaptability, and alignment), and supply chain resilience (SCR), addressing a significant gap in both theory and practice. While SCA has emerged as a transformative tool for managing disruptions through data-driven insights, its potential to foster resilience remains underexplored without the integration of dynamic organizational capabilities. Grounded in the dynamic capability’s theory, this research examines how SCA enhances Triple-A capabilities, which in turn drive SCR by enabling organizations to sense, respond to, and adapt to disruptions. Using a dual-study approach, our findings show that while alignment strongly predicts agility, it does not directly enhance adaptability, challenging conventional wisdom that greater alignment inherently strengthens both capabilities. These results suggest the need to reconsider linear assumptions about capability building in supply chains. Multiple analytical approaches and robustness checks, including alternative model specifications, different estimation techniques, and subgroup analyses, were performed to ensure research rigor. The consistent results across these analyses confirm the robustness and generalizability of the study’s findings. This study advances not only theoretical understanding by connecting SCA with the Triple-A supply chain and resilience but also provides actionable insights for practitioners to align investments in analytics with strategic organizational capabilities. By addressing these interconnections, this research contributes to bridging the gap between digital transformation and resilient supply chain practices, offering a robust framework for navigating uncertainty
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