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Understanding the Economic Impact of Oil Price Shocks
No full textThere is a rich literature on the link between oil price fluctuations and macroeconomic fundamentals that emerged after the oil shocks of the 1970s. This paper reviews this research and provides an overview of key historical developments in the global crude oil market and their implications for the oil price-macroeconomy relationship. We discuss theoretical and empirical studies on this theme with a focus on empirical issues researchers have had to overcome. We speculate that, as the world transitions to a low-carbon economy, oil is likely to continue losing market share to other energy sources and that this will lead to a secular decline in the importance of oil for the macroeconomy. But even in the most optimistic scenarios, this transition will take decades and, in the meantime, understanding oil price shocks will continue to be an area of active research
Understanding the Economic Impact of Oil Price Shocks
No full textThere is a rich literature on the link between oil price fluctuations and macroeconomic fundamentals that emerged after the oil shocks of the 1970s. This paper reviews this research and provides an overview of key historical developments in the global crude oil market and their implications for the oil price-macroeconomy relationship. We discuss theoretical and empirical studies on this theme with a focus on empirical issues researchers have had to overcome. We speculate that, as the world transitions to a low-carbon economy, oil is likely to continue losing market share to other energy sources and that this will lead to a secular decline in the importance of oil for the macroeconomy. But even in the most optimistic scenarios, this transition will take decades and, in the meantime, understanding oil price shocks will continue to be an area of active research
Complexes of groups and geometric small cancellation over graphs of groups
No full textWe explain and generalize a construction due to Gromov to realize geometric small cancelation groups over graphs of groups as fundamental groups of non-positively curved 2-dimensional complexes of groups. We then give conditions so that the hyperbolicity and some finiteness properties of the small cancelation quotient can be deduced from analogous properties for the local groups of the initial graph of groups
Two-Stage Learning Framework with a Beam Image Dataset for Automatic Laser Resonator Alignment
No full textAccurate alignment of a laser resonator is essential for upscaling industrial laser manufacturing and precision processing. However, traditional manual or semiautomatic methods depend heavily on operator expertise, and struggle with the interdependence among multiple alignment parameters. To tackle this, we introduce the first real-world image dataset for automatic laser resonator alignment, collected on a laboratory-built resonator setup. It comprises over 6,000 beam profiler images annotated with four key alignment parameters (intracavity iris aperture diameter, output coupler pitch and yaw actuator displacements, and axial position of the output coupler), with over 500,000 paired samples for data-driven alignment. Given a pair of beam profiler images exhibiting distinct beam patterns under different configurations, the system predicts the controlparameter changes required to realign the resonator. Leveraging this dataset, we propose a novel two-stage deep learning framework for automatic resonator alignment. In Stage 1, a multi-scale CNN augmented with cross-attention and correlation-difference modules, extracts features and outputs an initial coarse prediction of alignment parameters. In Stage 2, a feature-difference map is computed by subtracting the paired feature representations and fed into an iterative refinement module to correct residual misalignments. The final prediction combines coarse and refined estimates, integrating global context with fine-grained corrections for accurate inference. Experiments on our dataset and a different instance of the same physical system from which the CNN was trained suggest superior accuracy and practicality to manual alignment
Nature Connectedness and Well-Being: Evidence from a Multi-National Investigation Across 75 Countries
No full textNature connectedness, a widely used psychological construct which encompasses affective and cognitive aspect of the relationship a person has with nature, has become a central variable of interest in environmental psychology literature. This interest is motivated partially by its enhancing effects on well-being outcomes. However, comprehensive international evaluations of the link between nature connectedness and well-being remain sparse. In this registered report, we propose a secondary analysis of previously collected data to examine how individual differences in nature connectedness relate to multiple aspects of well-being (i.e., purpose in life, hope, mindfulness, life satisfaction, and optimism) across 75 countries (N = 36,803). Within-country and between-country analyses (linear and mixed regressions) suggested that nature connectedness is a robust positive predictor of well-being. Our findings highlight the importance of nature connected for well-being globally, especially for communities with low access to nature and social resources
Two-Stage Learning Framework with a Beam Image Dataset for Automatic Laser Resonator Alignment
No full textAccurate alignment of a laser resonator is essential for upscaling industrial laser manufacturing and precision processing. However, traditional manual or semiautomatic methods depend heavily on operator expertise, and struggle with the interdependence among multiple alignment parameters. To tackle this, we introduce the first real-world image dataset for automatic laser resonator alignment, collected on a laboratory-built resonator setup. It comprises over 6,000 beam profiler images annotated with four key alignment parameters (intracavity iris aperture diameter, output coupler pitch and yaw actuator displacements, and axial position of the output coupler), with over 500,000 paired samples for data-driven alignment. Given a pair of beam profiler images exhibiting distinct beam patterns under different configurations, the system predicts the controlparameter changes required to realign the resonator. Leveraging this dataset, we propose a novel two-stage deep learning framework for automatic resonator alignment. In Stage 1, a multi-scale CNN augmented with cross-attention and correlation-difference modules, extracts features and outputs an initial coarse prediction of alignment parameters. In Stage 2, a feature-difference map is computed by subtracting the paired feature representations and fed into an iterative refinement module to correct residual misalignments. The final prediction combines coarse and refined estimates, integrating global context with fine-grained corrections for accurate inference. Experiments on our dataset and a different instance of the same physical system from which the CNN was trained suggest superior accuracy and practicality to manual alignment
The Directive on the Credit Agreements for Consumers relating to Residential Immovable Property (Directive 2014/17): a Regulatory Explanation and a Private Law Analysis’
No full textWith the devastation wrought by the 2008 ‘property market bubble’ still fresh in the mind on one hand, and a spate of recent enthusiasm manifested in the ‘rush to the property ladder’ on the other, the newly enacted Directive 2014/17 seeks to strike a middle ground of reasonableness in the delicate and sensitive matter of the security granted by the buyer of a residential property. Against this background, the present contribution analyses, first and foremost, the norms of a regulatory nature introduced by the new EU piece of legislation and the attempt to shape a new category of consumer. Among these precepts, attention is particularly afforded to the principle, of a public nature, prescribing that the bank’s assessment to grant a mortgage shall be prevailingly based on the ability of the mortgagor to repay the debt, rather than on the expected (but undemonstrated) burgeoning future value of the property. Furthermore, the discussion focuses on the private law principles introduced by the Directive. Among these is the onus lying on the bank to provide adequate information about the terms and conditions of the mortgage. More interestingly, the directive at stake derogates from, and goes beyond, the notion of prohibition of ‘agreement of forfeiture’ existing in some civil law jurisdictions. This novelty, the ancillary legal provisions of art 28 of Directive 2014/17 as well as their impact on the system of civil proceedings and foreclosure existing in each country, provide fertile ground for a legal and comparative analysis
Towards automated Physical Internet system: Simulations of two privacy-protecting routing protocols
No full textThe purpose of this paper is to address the trust issue that leads to reluctance to share data within the logistics sector. This paper leverages the latest logistics paradigm concept Physical Internet (PI), and introduces two decentralised routing protocols for PI, focusing on their performance and impact on privacy by minimising data sharing. We use Agent-Based Modelling (ABM) and Monte Carlo (MC) simulations to evaluate the effectiveness of the protocols in optimising route quality, monetary costs and external costs in a realistic business setup on the Belgian scale. In addition, a sensitivity analysis was performed to assess the impact of response delays in a logistics network. Our research demonstrates the possibility of sharing less data without compromising the optimality of routes. We find that at our problem scale, trucks are the preferred mode when only considering monetary costs. Our findings also illustrate the significant impact of response delays and the handling capacity of intermodal hubs on the efficiency of route planning and the need for automation to improve PI systems’ reliability. We further suggest that trust issues should become one of the primary focuses for the current stage of PI research
How can we transition from lab to the real world with our HCI and HRI setups?
No full textIn this position paper, we present the issues we and others have found when moving from the controlled lab space into the field. We therefore recommend some dos and don'ts for facing the challenge of transferring your research prototype from the lab to the real world. During this transfer, we often encounter crucial disconnects between our envisaged evaluation protocol and real life, often related to differing user expectations outside controlled experimental interactions. The redeployment of complex systems in unfamiliar (and often dissimilar) environments presents additional challenges.In this paper, we present some example transitions in the fields of mobile HCI and HRI. Based on these experiences, we list the possible roadblocks that other researchers might encounter and provide guidelines and suggestions for dealing with frequently encountered issues. We hope that with this paper we can help stimulate the discussion on the pathway to undertaking scientifically reproducible evaluations in the wild
Complexes of groups and geometric small cancellation over graphs of groups
No full textWe explain and generalize a construction due to Gromov to realize geometric small cancelation groups over graphs of groups as fundamental groups of non-positively curved 2-dimensional complexes of groups. We then give conditions so that the hyperbolicity and some finiteness properties of the small cancelation quotient can be deduced from analogous properties for the local groups of the initial graph of groups
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