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Administrating crisis is just a transition : interventions on bureaucratic activity in the United Kingdom, 1987-2022
Full text linkThe process of leaving the European Union set off a disruptive transformation of the UK’s system of government. Central to implementing this process was secondary legislation, called statutory instruments, which received unparalleled levels of attention by the public due to the government’s use of them to untangle UK and EU law. Yet, the legislative crisis caused by Brexit, appeared in many ways just another form of government transition. We propose that understanding how this process affected bureaucratic activity requires a broad theory of regular partisan transitions. Large changes in the ideological goals and demands of the government redirect the priority of policies developed through instruments. To examine this perspective, we analyse the most prominent partisan and political transitions in the UK from 1987 to 2022 using time series intervention analyses. The results indicate that crises and transitions alike led to lasting changes in the bureaucracy’s agenda. Transitions in 2010 and 2015 not only exhibited shifts in the topical focus of secondary legislation, but also dramatic reductions in productivity. This paper’s findings further suggest that partisan effects on issue attention may have more to do with the organisation of government than the broader distribution of issues addressed using public policy
Civil engineering employers engagement in work-integrated learning
Full text linkIn this paper, two case studies of enhancing undergraduate students’ learning through work-integrated learning are presented. Both interventions involve university–industry partnerships with local and regional civil engineering employers. Industry Mentoring (2010–2024) is a curricular activity with an authentic assessment. Third-year student mentees (n = 1130) were mentored by 298 practising civil engineers, representing 80 employers. Civil Engineering 4 Real (CE4R, 2012–2024) is a co-curricular hybrid programme of problem/project-based evening workshops (n = 133), attended by 594 students with around 2867 student attendances, supported by 218 engineers, representing 76 employers. Industry Mentoring and CE4R support students to network with employers, enhance their employability skills, and shape their professional identity. Through their free assistance, employers have established a talent pipeline, recruiting students for summer placements and graduate jobs. For employers, their engagement provides evidence of enacting their corporate social responsibility through providing a social value contribution to a local university
Queer feminist teaching(s) in the university
No full textQueer feminist pedagogies can be understood in part as strategy for transforming academic hierarchies. We develop an expanded understanding of teaching(s) to encompass learning about power as we navigate the heteronormative and anti-feminist university. This expansive approach allows us to consider informal learning, between academic peers across university hierarchies, and the hard lessons learnt when we persist with making space for queer feminism. In this contribution, we set out our interruption methods and proceed to 1) explore how queer feminist negotiations of the academic career course teach us about power, 2) attend to queer feminist mentoring and its co-optation in leadership development schemes as another teachable moment and 3) look to how queer feminists, and their teaching, are made institutionally recognisable in equality initiatives such as Athena SWAN. Throughout we are concerned with contradictory expectations placed on queer feminists as problem solvers responsibilised for remediating institutional failures, and ask whether queer feminist teachers can embrace the 'failure' inherent in the role, as subversive and radical potential
3D-printed airflow hair sensor inspired by the buthus occitanus scorpion’s flat trichobothria
Full text linkThe adult Buthus occitanus scorpion has an interesting hair-like mechanoreceptor (called trichobothrium), which is flat instead of circular and allows great sensitivity for airflow measurements. The aim of this work is to develop a bioinspired artificial hair-like sensor (AHS) with a similar flat hair shaft using 3D printing. The sensor was successfully manufactured using digital light processing (DLP), a technique that allows multiple sensors to be 3Dprinted sensor in one batch, or arrays of them in a singular structure. The sensor is then sputter-coated with platinum to add piezoresistive capabilities and allow the transduction of airflow velocities into voltage levels. The sensor has been characterized to show a sensing range between 6.8 and 22.3 m/s and an average measurement error <1% under the tested conditions. The upper range warrants further study as it was limited by the experimental setup. The sensor can be used for several applications covering robotics, biomedical engineering, and meteorology, and the use of DLP allows for great customization capability
From system 1 to system 2 : a survey of reasoning Large Language Models
Full text linkAchieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in quick, heuristic decisions, System 2 relies on logical reasoning for more accurate judgments and reduced biases. Foundational Large Language Models (LLMs) excel at fast decision-making but lack the depth for complex reasoning, as they have not yet fully embraced the step-by-step analysis characteristic of true System 2 thinking. Recently, reasoning LLMs like OpenAI's o1/o3 and DeepSeek's R1 have demonstrated expert-level performance in fields such as mathematics and coding, closely mimicking the deliberate reasoning of System 2 and showcasing human- like cognitive abilities. This survey begins with a brief overview of the progress in foundational LLMs and the early development of System 2 technologies, exploring how their combination has paved the way for reasoning LLMs. Next, we discuss how to construct reasoning LLMs, trace the evolution of various reasoning models, and examine the core methods that enable advanced reasoning behind them. Additionally, we provide an overview of reasoning benchmarks, offering an in-depth comparison of the performance of representative reasoning LLMs. Finally, we explore promising directions for advancing reasoning LLMs and maintain a real-time GitHub Repository to track the latest developments. We hope this survey will serve as a valuable resource to inspire innovation and drive progress in this rapidly evolving field
Clay anisotropy : bridging the gap between micro and macro scales
No full textConstitutive models for anisotropic clays incorporate a tensor-valued quantity named the ‘fabric tensor’ to describe the direction-dependent mechanical response of the material. Although the term ‘fabric’ reflects the directional properties at the microscale, this tensor is not actually measured or observed at the microscale but formulated as a mathematical entity and calibrated by best-fitting experimental observations at the macro-scale. This paper presents a first attempt to bridge the gap between micro and macro scales by using direct measurements of the fabric tensor at the microscale to inform a continuum-based constitutive model. Owing to the scarcity of experimental measurements of the fabric in clayey geomaterials, this paper turns to virtual experiments using the discrete-element method (DEM) to quantify the microstructural arrangement and its evolution in response to imposed stress or strain history. The virtual experimental programme was performed in a simplified two-dimensional numerical framework and consisted of a set of virgin radial paths to generate different macroscopic anisotropic responses, quantified by way of the elastic stiffness in the horizontal and vertical direction. An existing constitutive model developed within the framework of thermodynamics with internal variables (TIV) was then used to describe the macroscopic behaviour of the DEM specimens, once the fabric-related parameters had been inferred from particle orientations. The DEM-based TIV model was proven to simulate satisfactorily the numerical compressibility curves for radial compression paths at different stress ratios and, most importantly, to reproduce well the macroscopic anisotropic elastic stiffness and its evolution
Can we formalise type theory intrinsically without any compromise? A case study in Cubical Agda
No full textWe present an intrinsic representation of type theory in the proof assistant Cubical Agda, inspired by Awodey's natural models of type theory. The initial natural model is defined as quotient inductive-inductive-recursive types, leading us to a syntax accepted by Cubical Agda without using any transports, postulates, or custom rewrite rules. We formalise some meta-properties such as the standard model, normalisation by evaluation for typed terms, and strictification constructions. Since our formalisation is carried out using Cubical Agda's native support for quotient inductive types, all our constructions compute at a reasonable speed. When we try to develop more sophisticated metatheory, however, the 'transport hell' problem reappears. Ultimately, it remains a considerable struggle to develop the metatheory of type theory using an intrinsic representation that lacks strict equations. The effort required is about the same whether or not the notion of natural model is used
Low-cost 3D printed optics for super-resolution multifocal structured illumination microscopy
No full textWe present a low-cost 3D-printing method of fabricating optical quality lenslet arrays for integration in a multifocal structured illumination microscope (mSIM), achieving super-resolution fluorescence imaging using 3D-printed optics for the first time. We detail the design and manufacturing processes to produce high-quality 3D-printed optics, showing their comparable surface roughness of 30 ± 2.5 nm for the 3D-printed elements compared to 37 ± 1.4 nm for commercial glass optics. A 3D-printed lenslet array with a 'honeycomb' geometry and 1.2 mm lenslet diameter was compared to a high-end glass commercial lenslet array with 250 µm lenslet diameter and a lower cost commercial lenslet array with a 1 mm by 1.4 mm lenslet footprint. The imaging performance of the different optics was benchmarked using a custom mSIM setup by quantifying the beam profile homogeneity and the experimental lateral resolution. The mSIM setup incorporating the different microlens arrays was tested using a commercial bovine pulmonary artery endothelial cell specimen, highlighting an achievable resolution enhancement from 237 nm ± 12 nm with laser-scanning illumination to 151 ± 12 nm using the high-end commercial microlens array and from 232 ± 18 nm with laser-scanning illumination to 151 nm ± 12 nm using the 3D-printed honeycomb lenslet array. Advantages of improved background rejection through the custom lenslet geometry are discussed, highlighting the super-resolution microscope performance achievable using custom 3D-printed optics costing as low as £0.50 to produce
Forecasting with machine learning Shadow-Rate VARs
No full textInterest rates are fundamental in macroeconomic modeling. Recent studies integrate the effective lower bound (ELB) into vector autoregressions (VARs). This paper studies shadow-rate VARs by using interest rates as a latent variable near the ELB to estimate their shadow-rate values. The study explores machine learning models, such as the Bayesian LASSO, and extends the analysis to include homoscedastic and stochastic volatility shadow-rate VARs. It also examines the integration of shadow rate with vintage-specific long-run assumptions derived from the Survey of Professional Forecasters (SPF). The paper analyzes 16 shadow-rate VARs with 20 US variables, using real-time data from 2005 to 2019 and assesses their predictive accuracy for both point and density forecasts. The findings indicate that shadow-rate models can enhance predictive accuracy for both short-term and longer term horizons across macroeconomic and financial variables. These models could be of use for central banks and policymakers
deportigualízate : enacting critical intersectional feminist pedagogy in Spanish PESTE
Full text linkBackground Physical education is seen as a subject that can both entrench but also challenge inequities. Within Spain, there is legislation requiring educators to teach about gender equity in schools across all subjects. Given this, topics around gender (and equity more broadly) are being taught in some Spanish Physical Education-Sport Tertiary Education (PESTE) programmes. Purpose The purpose of this paper is to explore university students’ experiences of engaging with a critical intersectional feminist pedagogy unit in a Spanish PESTE programme. Methods This paper represents one participatory action research study that is part of a larger research project exploring equity in physical education. The authors use qualitative data generation methods (including interviews, evaluations, field notes, and others) as well as data analysis (narrative analysis, descriptive coding, concept coding) to develop the findings. Findings The findings examine two teaching moments from the unit that students resonated with the most. In so doing, the authors examine the specific factors that the students discussed the most as affecting the way they think about equity in health, physical activity, and education. Conclusions The authors conclude by arguing that critical approaches to physical education that draw on embodied pedagogies and emplaced criticality have the ability to make ripples of change that can help raise issues of equity amongst future physical education professionals
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