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This article examines how emerging economies use countercyclical monetary policies to manage economic crises and fluctuations in dominant currencies, such as the US dollar and the euro. Global economic cycles are marked by phases of expansion and recession, often exacerbated by major financial crises. These crises, such as those of 1997, 2008 and the disruption caused by the COVID-19 pandemic, have a particular impact on emerging economies due to their heightened vulnerability to foreign capital flows and exports.Counter-cyclical monetary policies, including interest rate adjustments, foreign exchange interventions and capital controls, are essential to stabilize these economies. These measures aim to mitigate the effects of economic shocks, maintain price stability and promote sustainable growth. This article presents a theoretical analysis of economic cycles and financial crises, highlighting the role of dominant currencies in global economic stability. Currencies such as the dollar and the euro strongly influence emerging economies, notably through exchange rate variations and international capital movements. Analysis of the monetary strategies of emerging economies, through case studies of Brazil, India and Nigeria, reveals how these countries use tools such as interest rates, foreign exchange interventions and capital controls to manage the impacts of crises and fluctuations in dominant currencies. The article also highlights the challenges and limitations faced by these countries, including structural and institutional constraints and the reactions of international financial markets.Finally, an econometric analysis using a Vector AutoRegression (VAR) model illustrates the impact of monetary policies on key economic variables, such as GDP, interest rates, inflation and exchange rates. The results show that emerging economies, although sensitive to external shocks, can adjust their policies to stabilize economic growth in the medium and long term.

This article examines the economic effects of an increase in the duration of home loans on households, focusing on the French real estate market. It highlights trends in the property market, existing loan systems in other countries (such as bullet loans in Sweden and Japanese home loans), the current state of the property market in France, the potential effects of an increase in the amortization period of home loans, and the financial implications for households.The article points out that increasing the repayment period on home loans could reduce the amount of monthly instalments to be repaid, thereby facilitating access to credit for the most modest households. However, this measure also raises concerns about overall credit costs, financial stability and the impact on property prices. In addition, it highlights the differences between existing lending systems in other countries, such as the bullet loan in Sweden and Japanese home loans, and the current characteristics of home loans in France, notably interest rates and house price trends. The article proposes a model of the potential effects of an increase in the amortization period of home loans on housing demand, housing supply, property prices and the associated financial risks.In conclusion, the article highlights the crucial importance of household debt for individual and economic financial stability. It highlights the distortion between supply and demand for home loans as amortization periods increase, and the significant rise in overall loan costs for households. It also underlines the need to address structural issues such as the sustainable reduction in interest rates, the stabilization of banks' equity capital and the development of a regulatory framework for intergenerational lending to ensure a properly functioning market.

Fast and accurate qubit measurement remains a critical challenge on the path to fault-tolerant quantum computing. In superconducting quantum circuits, fast qubit measurement has been achieved using a dispersively coupled resonator with a large external linewidth. This necessitates the use of a Purcell filter that protects the qubit from relaxation through the readout channel. Here we show that a readout resonator and filter resonator, coupled to each other both capacitively and inductively, can produce a compact notch-filter circuit that effectively eliminates the Purcell decay channel through destructive interference. By utilizing linewidths as large as 42 MHz, we perform 56-ns simultaneous readout of four qubits and benchmark an average assignment fidelity of 99.77%, with the highest qubit assignment fidelity exceeding 99.9%. These results demonstrate a significant advancement in speed and fidelity for multiplexed superconducting qubit readout., Comment: 20 pages, 17 figures

Connected and automated vehicles and robot swarms hold transformative potential for enhancing safety, efficiency, and sustainability in the transportation and manufacturing sectors. Extensive testing and validation of these technologies is crucial for their deployment in the real world. While simulations are essential for initial testing, they often have limitations in capturing the complex dynamics of real-world interactions. This limitation underscores the importance of small-scale testbeds. These testbeds provide a realistic, cost-effective, and controlled environment for testing and validating algorithms, acting as an essential intermediary between simulation and full-scale experiments. This work serves to facilitate researchers' efforts in identifying existing small-scale testbeds suitable for their experiments and provide insights for those who want to build their own. In addition, it delivers a comprehensive survey of the current landscape of these testbeds. We derive 62 characteristics of testbeds based on the well-known sense-plan-act paradigm and offer an online table comparing 23 small-scale testbeds based on these characteristics. The online table is hosted on our designated public webpage https://bassamlab.github.io/testbeds-survey, and we invite testbed creators and developers to contribute to it. We closely examine nine testbeds in this paper, demonstrating how the derived characteristics can be used to present testbeds. Furthermore, we discuss three ongoing challenges concerning small-scale testbeds that we identified, i.e., small-scale to full-scale transition, sustainability, and power and resource management., Comment: 16 pages, 11 figures, 1 table. This work was accepted by the IEEE Robotics & Automation Magazine

The properties of functional oxide heterostructures are strongly influenced by the physics governing their interfaces. Modern deposition techniques allow us to accurately engineer the interface physics through the growth of atomically precise heterostructures. This enables minute control over the electronic, magnetic, and structural characteristics. Here, we investigate the magnetic properties of tailor-made superlattices employing the ferromagnetic and insulating double perovskites RE$_2$NiMnO$_6$ (RE = La, Nd), featuring distinct Curie temperatures. Adjusting the superlattice periodicity at the unit cell level allows us to engineer their magnetic phase diagram. Large periodicity superlattices conserve the individual para- to ferromagnetic transitions of the La$_2$NiMnO$_6$ and Nd$_2$NiMnO$_6$ parent compounds. As the superlattice periodicity is reduced, the Curie temperatures of the superlattice constituents converge and, finally, collapse into one single transition for the lowest period samples. This is a consequence of the magnetic order parameter propagating across the superlattice interfaces, as supported by a minimal Landau theory model. Further, we find that the Nd-Ni/Mn exchange interaction can be enhanced by the superlattice interfaces. This leads to a field-induced reversal of the Nd magnetic moments, as confirmed by synchrotron X-ray magnetic circular dichroism measurements and supported by first-principles calculations. Our work demonstrates how superlattice engineering can be employed to fine-tune the magnetic properties in oxide heterostructures and broadens our understanding of magnetic interfacial effects.

The study of non-line-of-sight (NLOS) imaging is growing due to its many potential applications, including rescue operations and pedestrian detection by self-driving cars. However, implementing NLOS imaging on a moving camera remains an open area of research. Existing NLOS imaging methods rely on time-resolved detectors and laser configurations that require precise optical alignment, making it difficult to deploy them in dynamic environments. This work proposes a data-driven approach to NLOS imaging, PathFinder, that can be used with a standard RGB camera mounted on a small, power-constrained mobile robot, such as an aerial drone. Our experimental pipeline is designed to accurately estimate the 2D trajectory of a person who moves in a Manhattan-world environment while remaining hidden from the camera's field-of-view. We introduce a novel approach to process a sequence of dynamic successive frames in a line-of-sight (LOS) video using an attention-based neural network that performs inference in real-time. The method also includes a preprocessing selection metric that analyzes images from a moving camera which contain multiple vertical planar surfaces, such as walls and building facades, and extracts planes that return maximum NLOS information. We validate the approach on in-the-wild scenes using a drone for video capture, thus demonstrating low-cost NLOS imaging in dynamic capture environments., Comment: First two authors have equal contribution

Ultra-hot Jupiters (UHJs) undergo intense irradiation by their host stars and are expected to experience non-local thermodynamic equilibrium (NLTE) effects in their atmospheres. Such effects are computationally intensive to model but, at the low pressures probed by high-resolution cross-correlation spectroscopy (HRCCS), can significantly impact the formation of spectral lines. The UHJ WASP-121 b exhibits a highly inflated atmosphere, making it ideal for investigating the impact of NLTE effects on its transmission spectrum. Here, we formally introduce Cloudy for Exoplanets, a Cloudy-based modelling code, and use it to generate 1-D LTE and NLTE atmospheric models and spectra to analyse archival HARPS WASP-121 b transmission spectra. We assessed the models using two HRCCS methods: i) Pearson cross-correlation, and ii) a method that aims to match the average observed line depth for given atmospheric species. All models result in strong detections of Fe I ($7.5