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Rational points in a family of conics over <sub>2</sub>(<i>t</i>)
Get PDFSerre famously showed that almost all plane conics over (Formula presented.) have no rational point. We investigate versions of this over global function fields, focusing on a specific family of conics over (Formula presented.) which illustrates new behavior. We obtain an asymptotic formula using harmonic analysis, which requires a Tauberian theorem over function fields for Dirichlet series with branch pointย singularities.</p
The Influence of Axial Throughflow Swirl on Buoyancy-Induced Flow in a Compressor Cavity
Get PDFNext-generation aero-engine compressors will operate with overall pressure ratios exceeding 70:1. This will require shorter compressor blades, presenting a challenge to the designer when predicting tip clearance and efficiency. Buoyancy-induced flow within co-rotating compressor discs drives the heat transfer that determines rotor expansion and the resulting blade-tip clearance. This inherently unstable flow is influenced by the radial temperature distribution of the discs, rotational speed, as well as enthalpy and momentum exchange with an axial throughflow of cooled air at low radius. Due to the rotation of the engine compressor, this throughflow may become swirled, altering the temperature, mass exchange, and swirl within the rotating cavity. The University of Bath Compressor Cavity Rig has been adapted to introduce preswirl into the axial throughflow by passing it through rotating holes. The effects of inlet swirl have been characterized in terms of Rossby and Reynolds numbers. Measurements of disc temperature, shroud heat flux, and unsteady pressure in the rotating frame of reference are used to quantify the effects of ingestion (entrainment) of fluid into the cavity. The unsteady dynamics and rotation of the core relative to the disc have been measured in both the stationary and rotating frames of reference with consistent results. A single correlation between shroud Nusselt and Grashof numbers has been established, effectively capturing the impact of swirl, Rossby number, and free convection
Electoral politics over automation in a dual economy
Get PDFWhen automation in a developing economy displaces low-skilled workers in the advanced sector, backward sector wages may fall due to in-migration of the โnewlyโ unemployed. Fear of job and income loss may then induce office-seeking political parties to announce regulatory policies on automation for electoral success. We show that absent sectoral spillover, democratic adoption of automation is relatively higher and protects only high-skilled jobs in the advanced sector. However, the possibility of spillover limits this adoption. More specifically, if the backward sector is large, automation faces full resistance. In contrast, if the advanced sector is large, automation is moderate, making only the low-skilled jobs vulnerable. But these vulnerable workers, unlike their counterparts in the backward sector, may prefer automation because their advanced-sector wages fall below the severance pay plus backward-sector opportunities. When neither sector is large, the size of automation becomes uncertain, pushing similar economies into different growth paths
Getting the most from your data:Using Statistical Process Controls for Data Quality Assurance in Sport Science Data
Get PDFAll levels of sport have seen a surge in data availability, which has allowed for the prospective and retrospective monitoring and tracking of player performance metrics, physical outputs (e.g., distance run, number of accelerations), and injuries. Players, coaches, support staff, governing bodies, and researchers are trying to leverage data to support long-term player welfare and real-time decisions, and this is made possible with advances in data capture, processing, and analysis. Statistical process control (SPC) is a method of quality control designed for understanding, monitoring, and improving process performance over time, historically associated with manufacturing. Visualization of SPC, referred to as a run chart, is accompanied by a mean centerline to show how the underlying process is changing relative to a benchmark. The run chart is visualized with control limits, which are used to determine whether the process is, or is not, operating within statistical control. Deviation of process data outside of the control limits is deemed to be a cause for special variation, highlighting areas that may require investigation. The aims of this methodological report are (a) to provide an example of how SPC can be used in sport and athlete monitoring and (b) provide practical applications for the sports science practitioner. This tutorial provides specific examples from the author's experience in using SPC in the sport field and adjoining simulated data and code to reproduce these results, and more importantly, use as a template for the practitioner's own sport data
Large-amplitude periodic solutions to the steady Euler equations with piecewise constant vorticity
Get PDFWe consider steady solutions to the incompressible Euler equationsย in a two-dimensional channel with rigid walls. The flow consists of two periodic layers of constant vorticity separated by an unknown interface. Using global bifurcation theory, we rigorously construct curves of solutions that terminate either with stagnation on the interface or when the conformal equivalence between one of the layers and a strip breaks down in a (Formula presented.) sense. We give numerical evidence that, depending on parameters, these occur either as a corner forming on the interface or as one of the layers developing regions of arbitrarily thin width. Our proof relies on a novel formulation of the problem as an elliptic system for the velocity components in each layer, conformal mappings for each layer, and a horizontal distortion, which makes these mappings agree on the interface. This appears to be the first local formulation for a multi-layer problem, which allows for both overhanging wave profiles and stagnationย points.</p
A theory of change approach to enhance the post-2030 sustainable development agenda
Get PDFAs the 2030 deadline for the Sustainable Development Goals(SDGs) nears and progress remains limited, researchers are proposing measuresto enhance the next, post-2030, agenda to improve implementation (1โ3). Withmore proposals expected in future, we argue for a systematic approach to helpresearchers and policy-makers design and assess them. This requires a theory ofchange that explains how and why proposals will improve implementation of thenext agenda, while also considering their political feasibility. We start byconstructing an implicit theory of change underpinning the current 2030 Agenda(4) to revisit how the SDGs were intended to work and identify key successesand failures. We then propose an approach for assessing proposals put forwardto improve the post-2030 agenda on the basis of their impact and feasibility.ย A better approach is needed to assess potential impact and feasibility of proposals.<p/
ConcreteShellFEA: A surrogate modelling dataset for the buckling and stress behaviour of concrete thin-shells
No full textConcreteShellFEA is a dataset designed for the training of deep learning models to predict buckling loads and stress fields in concrete thin-shell structures. It contains 3 smaller datasets, which can be used for different use cases: 1. PerfectShell_LinearFEA: A dataset of 20,000 thin-shells (with various span, height, thickness, and Young's modulus), for which buckling factors and stress fields under design loads were determined using linear Finite Element analysis. The data is presented in three formats (tabular, image, graph) to enable different types of deep learning models (Multilayer Perceptrons, Convolutional Neural Networks, and Graph Neural Networks) to be trained. 2. ImperfectShell_LinearFEA: A dataset of 20,000 imperfect thin-shells (with various span, height, thickness, Young's modulus, and geometric imperfections), for which buckling factors and stress fields under design loads were determined using linear Finite Element analysis. The data is presented in two formats (tabular, image) to enable different types of deep learning models (Multilayer Perceptrons, Convolutional Neural Networks) to be trained. 3. PerfectShell_NonlinearFEA: A dataset of 25,000 thin-shells (with various span, height, thickness, and Young's modulus, and geometric imperfections), for which buckling factors under design loads were determined using Finite Element analysis. The buckling factors were determined using linear Finite Element analysis for 20,000 thin-shells, and using nonlinear Finite Element analysis for 5,000 thin-shells, to enable mixed-fidelity applications. The data is presented in a single format (tabular)
Open Strategy as Institutional Work
Get PDFPurposeThis article positions institutional work as a central construct in open strategy research. While open strategy is widely celebrated for fostering transparency and inclusion, its potential as a mechanism for field-level institutional change remains underexplored. The study examines how managed openness enabled UK universities to perform institutional work that reshaped research culture and institutional logics in response to evolving field expectations around equality, diversity, and transparency.Design/methodology/approachDrawing on 17 in-depth interviews with senior leaders and 25 documentary sources from the N8 group of UK research-intensive universities, the study applies the Gioia methodology and critical discourse analysis to trace how open strategy practices were mobilized to enact institutional work. The analysis identifies three interrelated processes โ motivating, signalling, and enacting โ through which openness was purposefully managed to facilitate cultural and institutional transformation.FindingsOpen strategy practices operated as discursive, symbolic, and material mechanisms of institutional work. By framing change imperatives, demonstrating commitment, and empowering participation, leaders used managed openness to align organizational practices with emergent field-level logics. These processes culminated in research culture action plans that institutionalized new norms of transparency and inclusion across the N8 universities.Originality/valueThe article advances open strategy theory by establishing institutional work as a powerful lens for understanding how openness extends beyond organizational boundaries to orchestrate field-level change. It also introduces institutional critique as a precursor to institutional work, highlighting the role of elite actors and discursive legitimation in shaping openness as a strategic and institutional practice.<br/
Teacher agency in practiced language policy in higher education in East and Southeast Asia (2010โ2025):A systematic review
Get PDFThis paper presents the first systematic review connecting Teacher Agency (TA) and Practiced Language Policy (PLP) in English-medium instruction (EMI) within higher education (HE) across East and Southeast Asia. Following the PRISMA protocol, the review included twenty empirical studies published from 2010 to early 2025. Patterns of TA development and the pathways supporting them were identified through visualized co-occurrence. Findings show that agency is developmental and shaped by institutional arrangements, professional learning, and identity commitment. Classroom outcomes play a critical role in informing TA when implementing translanguaging, reassessing program and institutional contexts. A 3 ร 3 Integrated Model was proposed viewing PLP as Context, TA as Action, and practiced policy as Outcomes across macro, meso, and micro levels. This model provides actionable insights for optimizing resource allocation at critical decision points, granting contextual autonomy at the program level, and integrating professional development with the cyclical process of policy interpretation, reframing, and enactment.</p
SPAN:Learning Similarity between Scene Graphs and Images with Transformers
Get PDFLearning similarity between scene graphs and images aims to estimate a similarity score given a scene graph and an image. There is currently no research dedicated to this task, although it is critical for scene graph generation and downstream applications. Scene graph generation is conventionally evaluated by Recall@K and mean Recall@K, which measure the ratio of predicted triplets that appear in the human-labeled triplet set. However, such triplet-oriented metrics fail to demonstrate the overall semantic difference between a scene graph and an image and are sensitive to annotation bias and noise. Using generated scene graphs in the downstream applications is therefore limited. To address this issue, for the first time, we propose a Scene graPh-imAge coNtrastive learning framework, SPAN, that can measure the similarity between scene graphs and images. Our novel framework consists of a graph Transformer and an image Transformer to align scene graphs and their corresponding images in the shared latent space. We introduce a novel graph serialization technique that transforms a scene graph into a sequence with structural encodings. Based on our framework, we propose R-Precision measuring image retrieval accuracy as a new evaluation metric for scene graph generation. We establish new benchmarks on the Visual Genome and Open Images datasets. Extensive experiments are conducted to verify the effectiveness of SPAN, which shows great potential as a scene graph encoder.</p
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