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The financial crisis of 2007-8 has already revolutionized institutions, markets, and regulation. Wright's Money and Banking V 2.0 captures those revolutionary changes and packages them in a way that engages undergraduates enrolled in Money and Banking and Financial Institutions and Markets courses. |
As a high-impact educational practice, service-learning has demonstrated success in positively influencing students’ overall development, and much work has been done on investigating student learning outcomes from service-learning. A particular direction is to model students’ learning outcomes in the context of their learning experience, i.e., the various student, course, and pedagogical elements. It contributes to a better understanding of the learning process, a more accurate prediction of students’ attainments on the learning outcomes, and improvements in the design of learning activities to maximize student learning. |
We estimate new indices measuring financial and economic uncertainty in the euro area, Germany, France, the United Kingdom and Austria, following the approach of Jurado et al. (Am Econ Rev 105:1177–1216, 2015), which measures uncertainty by the degree of predictability. We perform an impulse response analysis in a vector error correction framework, where we focus on the impact of both local and global uncertainty shocks on industrial production, employment and the stock market. We find that global financial and economic uncertainties have significant negative effects on local industrial production, employment, and the stock market, while we find hardly any influence of local uncertainty on these variables. |
In this paper, we study the nonuniform fast Fourier transform with nonequispaced spatial and frequency data (NNFFT) and the fast sinc transform as its application. The computation of NNFFT is mainly based on the nonuniform fast Fourier transform with nonequispaced spatial nodes and equispaced frequencies (NFFT). The NNFFT employs two compactly supported, continuous window functions. For fixed nonharmonic bandwidth, we show that the error of the NNFFT with two sinh
-type window functions has an exponential decay with respect to the truncation parameters of the used window functions. As an important application of the NNFFT, we present the fast sinc transform. |
Being able to provide counterfactual interventions—sequences of actions we would have had to take for a desirable outcome to happen—is essential to explain how to change an unfavourable decision by a black-box machine learning model (e.g., being denied a loan request). Existing solutions have mainly focused on generating feasible interventions without providing explanations of their rationale. Moreover, they need to solve a separate optimization problem for each user. |
Our work exposes the structure of the template-based micro-kernels for ARM Neon (128-bit SIMD), ARM SVE (variable-length SIMD) and Intel AVX512 (512-bit SIMD), showing considerable performance for an NVIDIA Carmel processor (ARM Neon), a Fujitsu A64FX processor (ARM SVE) and on an AMD EPYC 7282 processor (256-bit SIMD). |
We introduce a persistent Hochschild homology framework for directed graphs. Hochschild homology groups of (path algebras of) directed graphs vanish in degree i≥2. To extend them to higher degrees, we introduce the notion of connectivity digraphs, and analyse two main examples; the first, arising from Atkin’s q-connectivity, and the second, here called n-path digraphs, generalising the classical notion of line graph. Based on a categorical setting for persistent homology, we propose a stable pipeline for computing persistent Hochschild homology groups. This pipeline is also amenable to other homology theories; for this reason, we complement our work with a survey on homology theories of directed graphs. |
Energy generated by land-based wind power is expected to play a crucial role in the decarbonisation of the economy. However, with the looming biodiversity and nature crises, spatial allocation of wind power can no longer be considered solely a trade-off against local disamenity costs. Emphasis should also be put on wider environmental impacts, especially if these challenge the sustainability of the renewable energy transition. We suggest a modelling system for selecting among a pool of potential wind power plants (WPPs) by combining an energy system model with a GIS analysis of WPP sites and surrounding viewscapes. The modelling approach integrates monetised local disamenity and carbon sequestration costs and places constraints on areas of importance for wilderness and biodiversity ... |
The Sustainable Business Case Book by Gittell, Magnusson and Merenda is one of the first of its kind. It combines the the theory of sustainability with key concepts, analytical information and contextual information with a collection of cases which provide insights, perspective and practical guidance on how sustainable businesses operate from different business functional area perspectives. |
Wildfires affect countries worldwide as global warming increases the probability of their appearance. Monitoring vast areas of forests can be challenging due to the lack of resources and information. Additionally, early detection of wildfires can be beneficial for their mitigation. To this end, we explore in simulation the use of swarms of uncrewed aerial vehicles (UAVs) with long autonomy that can cover large areas the size of California to detect early stage wildfires. Four decentralised control algorithms are tested: (1) random walking, (2) dispersion, (3) pheromone avoidance and (4) dynamic space partition. |
