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Economic history and the future of pedagogy in economics
No full textEconomic history is an essential component of the study of economics and economies. It offers students a long-run perspective on the development of the modern world and fosters a deeper appreciation of the historical contingency of economic theory. Despite renewed interest in the field among economists, the provision of economic history teaching at undergraduate level in the UK remains highly uneven. This article surveys the diverse approaches to undergraduate economic history education across UK universities, explores the underlying causes of this variation, and proposes practical pathways for reform. We advocate for a model we term “Teaching Economics With Economic History”, in which economic history can be embedded within advanced undergraduate field courses rather than taught as stand-alone modules
Metasurfaces-enabled wave computing for future wireless systems: opportunities and challenges
No full textWhat Pareto-efficiency adjustments cannot fix
No full textThe Deferred Acceptance (DA) algorithm is stable and strategy-proof, but can produce matchings that are Pareto-inefficient for students, and thus several alternatives have been proposed to correct this inefficiency that only involve consented priority violations. However, we show that these approaches cannot correct DA's suboptimal rank distribution, because this shortcoming can arise even in cases where DA is Pareto-efficient.We also examine student segregation in settings with tiered priority structures. We prove that the demographic composition of every school is perfectly preserved under any Pareto-efficient rule that dominates DA, and consequently fully segregated schools under DA maintain their extreme homogeneity
Speculation in the UK, 1785-2019
No full textSpeculation has long been thought to have significant economic effects, but it is difficult to measure, making it challenging to examine these effects empirically. In this paper we measure speculation in the UK since 1785 by using business and financial reporting in The Times newspaper. Our monthly speculation index reveals four distinct epochs of speculation in the UK. Epochs of high speculation coincide with higher stock market returns and higher economic growth, while low speculation periods coincide with high levels of government debt and financial repression. We find that low interest rates foment the development of higher speculation, and that eras of higher speculation are often followed by greater banking instability
A half-mode CSIW leaky-wave antenna with horizontal beam-scanning and stable radiation
No full textConventional leaky-wave antennas (LWAs) typicallyscan their beams through the broadside direction, while designscapable of side-fire beam-scanning are significantly less common. This paper presents a wideband horizontal beam-scanningLWA with stable radiation characteristics, based on a halfmode corrugated substrate integrated waveguide (HMCSIW).The antenna’s leaky-wave radiation response is realized byadding square rings to the ground plane of the HMCSIW.Furthermore, the incorporation of circular rings on the antenna’sfront surface enhances the stability of the side-fire beam-scanningperformance. The proposed antenna achieves horizontal beamscanning over a frequency range of 13 to 22.5 GHz, correspondingto a 53.5% bandwidth. It exhibits a peak gain of 12.7 dBi witha maximum variation of 2.1 dBi, a beam-scanning range from -35° to 35°, and an average efficiency of approximately 90%. Theproposed antenna can be an intriguing choice for microwaveimaging applications, spectrum analysers, and next-generationradar systems
Joint OFDM radar-communications in complex mmWave environments
No full textHigh data rate millimetre-wave (mmWave)communication systems in dense, multi-user environments face major challenges, including strong interference, wideband noise, latency in mobile platforms, multipath reflections, and complex beamforming and hardware requirements. To tackle these issues, this paper explores a joint radar-communication(JRC) framework designed for highly dynamic scenarios involving mobile and aerial users. The proposed JRC system utilises radar's sensing capabilities to map the communication environment, enabling adaptive beamforming and optimising both phase-scanning and MIMO techniques. A central contribution of this work is the development of adaptive matched noise filters and techniques for scene reconstruction and interference cancellation, using blind source separation and successive interference cancellation. Additionally, the paper introduces radar waveform designs that improve signal orthogonality and separation between radar and communication functions. These advances demonstrate the potential of JRC systems for next-generation UAV communications and dense mmWave networks in fast changing, complex environment
Electromagnetic wave interaction and beam steering in plasma medium
No full textThis paper presents the effects of electromagnetic wave interaction with plasma medium and its application for wave manipulation as a use-case scenario. An efficient one-dimensional (1D) finite-difference time domain (FDTD) approach is used to model the wave propagation through the plasma medium at different plasma densities in transmission mode and reflection mode backed by a perfect electric boundary. Furthermore, the beam steering properties of the plasma for an incoming wave are studied and the results are reported. This study supports the development of plasma based reconfigurable surfaces, offering advantages in tunability, stealth and adaptive system designs.<br/
Inferring yielding intentions for safe and trustworthy vehicle interactions
No full textAutonomous driving technology has progressed rapidly since its emergence, and the coexistence of autonomous vehicles (AVs) with human-driven vehicles (HVs) on public roads is becoming increasingly likely. Currently, safety and reliable decision-making remain significant challenges, particularly when AVs are navigating lane changes and interacting with surrounding HVs. Therefore, precise estimation of the intentions of surrounding HVs can assist AVs in making more reliable and safe lane change decision-making. This involves not only understanding their current behaviors but also predicting their future motions without any direct communication. However, distinguishing between the passing and yielding intentions of surrounding HVs still remains ambiguous. To address the challenge, we propose a social intention estimation algorithm rooted in Directed Acyclic Graph (DAG), coupled with a decision-making framework employing Deep Reinforcement Learning (DRL) algorithms. To evaluate the method’s performance, the proposed framework can be tested and applied in a lane-changing scenario within a simulated environment. Furthermore, the experiment results demonstrate how our approach enhances the ability of AVs to navigate lane changes safely and efficiently on roads