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Podcast Series: The UN Sustainable Development Goals and Educational Research Implications for Policy and Practice.
Full text linkA podcast series hosted by the British Educational Research Association (BERA), in association with the UN Impact Hub.In 2015, United Nations Member States adopted the 2030 Agenda for Sustainable Development, which is framed around 17 Sustainable Development Goals (SDGs). The UN describes these goals as “an urgent call for action by all countries,” emphasizing the importance of global partnerships.
This podcast series explores the intersections of Higher Education (HE) and the United Nations Sustainable Development Goals (SDGs). Curated by Richard Hall and Kate Mawson, this series delves into how HE can respond to the urgent call for action set out in The 2030 Agenda for Sustainable Development. Adopted by United Nations Member States in 2015, the agenda envisions global peace and prosperity for people and the planet, centered on 17 transformative goals.
While SDG 4, Quality Education, stands as a direct link to HE, the implications stretch far beyond this single goal. Higher education institutions hold a unique and powerful role in advancing understanding, reducing inequalities, and fostering innovation across all SDGs—whether addressing gender equality (SDG 5), climate action (SDG 13), or partnerships for the goals (SDG 17).
This podcast series emerges from a collaborative initiative co-facilitated by the British Educational Research Association (BERA) Higher Education and Social Theory Special Interest Groups. At its core, the project aims to explore how HE policy and practice can engage with and impact the SDGs. It invites academics, practitioners, and policymakers to examine the intersections of HE with personal, social, ecological, and resource needs, including poverty eradication, sustainable cities, clean energy, and justice
Exploring novel aromatase cytochrome P450-binding ligands: Molecular docking and QSAR study of phorbol esters as aromatase inhibitors
No full textopen access articleA library comprising thirty-three natural and semi-synthetic phorbol derivatives was constructed and subsequently evaluated for aromatase (CYP19A1) inhibitory activity. The primary goal was to identify novel aromatase inhibitors through selective esterifications at the C-12, C-13 and C-20 positions of the phorbol skeleton. Twenty-two phorbol esters, fifteen of which were previously undescribed (5–9, 12 and 16–24), were obtained via semi-synthetic modifications. Additionally, ten 12-deoxyphorbol esters (25–34), four bearing an extra acyloxy chain at C-16, isolated from Euphorbia resinifera, were tested. Inhibition studies revealed that 12,13-diesters bearing medium-sized ester moieties (such as isobutyrate, tigliate or phenylacetate) exhibited the highest potency (IC50 = 0.9–6.4 μM). Conversely, shorter or longer ester chains significantly reduced activity (IC50 values ranging from 22.4 to 29.8 μM). An enhancement of potency was observed upon reduction of the α,β-unsaturated ketone at C-3 to an allylic alcohol. Molecular docking suggested that the phorbol derivatives bind within the aromatase activator-binding pocket, exerting their inhibitory actions through hydrogen-bond interactions with protein residues, independent of the heme group. The inhibitory potency correlated with the ability to establish these interactions. The activities of the most potent compounds are comparable to nonsteroidal, non-heme-binding aromatase inhibitors, such as stilbene and coumarin derivatives. Moreover, 3D-QSAR models were developed, with the most robust model (R2 = 0.908) highlighting the molecular descriptors NQC14 and AP as crucial modulators of the anti-aromatase activity. These findings provide a framework for future optimization of phorbol ester as selective aromatase inhibitors
UGAE: Unified Geometry and Attribute Enhancement for G-PCC Compressed Point Clouds
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.Lossy compression of point clouds reduces storage and transmission costs; however, it inevitably leads to irreversible distortion in geometry structure and attribute information. To address these issues, we propose a unified geometry and attribute enhancement (UGAE) framework, which consists of three core components: post-geometry enhancement (PoGE), pre-attribute enhancement (PAE), and post-attribute enhancement (PoAE). In PoGE, a Transformer-based sparse convolutional U-Net is used to reconstruct the geometry structure with high precision by predicting voxel occupancy probabilities. Building on the refined geometry structure, PAE introduces an innovative enhanced geometry-guided recoloring strategy, which uses a detail-aware K-Nearest Neighbors (DA-KNN) method to achieve accurate recoloring and effectively preserve high-frequency details before attribute compression. Finally, at the decoder side, PoAE uses an attribute residual prediction network with a weighted mean squared error (W-MSE) loss to enhance the quality of high-frequency regions while maintaining the fidelity of low-frequency regions. UGAE significantly outperformed existing methods on three benchmark datasets: 8iVFB, Owlii, and MVUB. Compared to the latest G-PCC test model (TMC13v29), in terms of total bitrate setting, UGAE achieved an average BD-PSNR gain of 9.98 dB and -90.54% BD-bitrate for geometry under the D1 metric, as well as a 3.34 dB BD-PSNR improvement with -55.53% BD-bitrate for attributes. Additionally, it improved perceptual quality significantly. Our source code will be released on GitHub at: https://github.com/yuanhui0325/UGA
Leicestershire Collaborate to Accelerate Net Zero : Final Insights Report on Local Area Energy Plan (LAEP) Governance and Place based Collaboration
No full textThis report outlines the key actions undertaken, impacts achieved and insights generated through delivery of Work Package 1 (WP1) of Leicestershire Collaborate to Accelerate Net Zero (LCAN). WP1 focused on establishing enabling governance arrangements towards the delivery of clean energy projects identified through the Leicestershire Local Area Energy Plan (LAEP).
The approach undertaken for WP1 was to be evidence-based and to undertake action-research with local and regional project partners so that approaches to governance and collaboration were realistic, desirable and agreed by those bodies directly involved, principally local authorities across Leicester, Leicestershire and Rutland (LLR).
The key innovation of WP1 came from the action-research focus of our work, with university staff directly collaborating with and convening stakeholders from local government and beyond in the LLR subregion, as well as advising and influencing local authority officers on impactful and innovative practices identified from across the UK. Positioning a network of universities as ‘apolitical’ actors which can act and convene for local public benefit was an innovative approach to overcome some barriers to joint working between local government actors. The project also established a strong evidence base on factors supporting and hindering local government-influenced energy project development and delivery within UK regions, particularly those without a combined or strategic authority structure.
The key deliverable of WP1 was an agreed approach to take forward collaborative delivery of the Leicester and Leicestershire LAEP, convened by the Universities Partnership for LLR. This comprises a ‘Clean Energy Project Community of Practice’, largely made up of local government officers, coupled with a strategic collaboration focussed upon enabling energy project investment at scale across LLR. The announcement of local government reorganisation during the delivery period and uncertainty about the future of local government in LLR hampered efforts to establish a well-resourced and long-term governance approach to drive delivery of LAEP projects. This led to agreement on ‘interim’ regional governance approaches, in advance of a likely future LLR Strategic Authority.
Overall, LCAN has had a significant impact in the Leicestershire area, in particular by developing an innovative LAEP which provides a robust evidence base for future clean energy project investment in future years. Funding for staff roles across a range of project partners has been a major investment in developing mutual trust and collaboration between a range of stakeholder bodies and individuals which will have a lasting legacy beyond the funded period
Resolving Conflicting Goals in Manufacturing Supply Chains: A Deterministic Multi-Objective Approach
No full textopen access articleIn the context of manufacturing logistics, this study sheds light on the difficult task of concurrently optimizing cost, time, influence on sustainability, and spatial efficiency. Specifically, this addresses the integrated challenge of material handling equipment selection and facility space allocation, a crucial decision-making domain where conventional single-objective methodologies frequently overlook vital considerations. While recent research predominantly relies on meta-heuristics and simulation-based solution methodologies, they do not guarantee a global optimum solution space. To effectively address this multifaceted decision environment, a Mixed-Integer Linear Programming (MILP) model is developed and resolved utilizing two distinct scalarization methodologies: the conventional ϵ-constraint method and the augmented ϵ-constraint method (AUGMECON2). The comparative analysis indicates that although both methods effectively identify the Pareto front, the AUGMECON2 approach offers a more robust assurance of solution efficiency by incorporating slack variables. The results illustrate a convex trade-off between capital expenditure and operational flow time, indicating that substantial reductions in time necessitate strategic investments in higher-capacity equipment fleets. Furthermore, the analysis underscores a significant conflict between achieving extreme operational efficiency and adhering to facility design standards, as reducing time or energy consumption beyond a specific point requires deviations from optimal space allocation policies. Ultimately, a “Best Compromise Solution” is determined that harmonizes near-optimal operational efficiency with strict compliance to spatial constraints, providing a resilient framework for sustainable manufacturing logistical planning
Evaluating the Impact of Lighting Conditions on Workers' Safety and Health in Industrial Settings
No full textopen access articleLighting is a key element of design that plays an important role in affecting workers’ health and safety in industrial workspaces. Given the scarcity of scientific studies addressing visual environments in relation to workers health in industrial buildings, this field study was conducted to explore workers' responses to multiple lighting scenarios inside production halls on their occupational health and safety in six factories in Sadat City, Egypt. Self-assessments of 456 factory workers during day and night shifts were collected and correlated to light measurements collected at the factories. The statistical analysis of data revealed a significant reduction in workers reporting eye strain, alleviating headaches, and enhancing the ability to concentrate under daylight conditions compared to mixed and/or artificial lighting conditions. Moreover, it was found that lighting levels lower than 140 lux led to visual fatigue(p=0.03), headaches (p=0.014), drowsiness (p=0.004), and rapid loss of concentration (p=0.149) among workers. Poor lighting was shown to increase the likelihood of making occupational errors. Despite the health benefits of natural light compared to artificial lighting, glare from sunlight can sometimes cause headaches. This study emphasizes the importance of improving lighting quality in production halls within industrial environments, as it is a crucial factor in maintaining the health and safety of workers and enhancing professional performance
Dynamic multi-objective optimization algorithm based on historical collaborative strategy and interval prediction strategy
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.Dynamic multi-objective optimization problems (DMOPs) involve scenarios where objective functions, decision variables, parameters, or other elements vary over time. An effective approach to address DMOPs is to integrate algorithms designed for static multi-objective optimization problems with dynamic response strategies. To improve the performance of these strategies in terms of both population diversity and convergence, this paper proposes a novel dynamic response strategy, the historical collaborative and interval prediction strategy (HCIPS). When confronted with environmental changes, we conduct a three-level population analysis: overall, historical, and individual. Firstly, the interval-based response strategy identifies interval partitioning of a population at time, enabling global localization of the predicted population and effectively preserving diverse population information. Secondly, the history-based response strategy guides the population movement by selecting optimal solutions from historical populations. Thirdly, the individual-based response strategy predicts individual positions by tracking the movement of key points. This serves as a crucial complement to the history-based response strategy, compensating for its primary drawback: a lack of sufficient historical data in the early stages of evolution. Experimental results indicate that the HCIPS offers advantages in solving DMOPs compared to past state-of-the-art algorithms
Influence of Cutting Parameters and Assist Gases on the Laser Cutting Quality of 09G2S (S355J2, EN 10025-2) Structural Steel
No full textopen access articleThis study aims to investigate and compare the structural, morphological, and phase transformations occurring in low-alloy steel 09G2S during laser cutting when using air and pure oxygen as assist gases. The study aims to investigate the impact of gas type on cut quality, heat-affected zone (HAZ) characteristics, oxidation, and potential defect formation. The experiments were conducted on 16 mm thick sheets using an 8 kW fibre laser under optimised conditions. Optical microscopy, scanning electron microscopy, as well as X-ray diffraction analysis were used to assess the HAZ. The results show that during air blowing, an uneven cutting surface, the formation of an oxidized layer up to 200 μm thick, and the formation of martensite in the near-surface zone are observed, due to an increased heat load and inefficient melt removal. While the use of oxygen ensures a more stable cutting process, resulting in an even and clear edge with a homogeneous microstructure in the HAZ and a reduced oxide content. Elemental analysis confirmed the low oxidation state and the absence of hydrogen in oxygen cutting, which minimizes the risk of flocken formation
The Wolfe Island Archive
No full textThe Wolfe Island Archive exists as a Blog.Throughout time historical periods have been identified by the things that were produced and the technologies used to create them. This exhibition asks ‘what will we leave behind?’ and ‘how will we be remembered?’
Mary O’ Neill’s practice drawings inspiration from museum objects and the structures and methods of museums themselves to produce work that re-vivifies objects that have lost their use value by being entombed in the museum. A necessary part of preservation is the compromise that objects that were made to be used, touched, worn, that has ritual value, must now be kept in a highly controlled environment where the knowledge they embody is often reduced to their appearance and aesthetic value.
For The Wolfe Island Archive O’Neill has produced a ‘hoard’ of artefacts allegedly found on an uninhabited island. The accompanying narrative describes the discovery of the hoard; the research carried out on the island and ultimately the reason for the demise of its inhabitants
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