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How to build a Ukrainian Development Bank: Leveraging European history and Ukraine’s own reform experience
No full textVoxEU-CEPREstablishing a Ukrainian Development Bank is key to Ukraine’s post-war recovery, to foster both international trust and local ownership. This column describes how, drawing on lessons from the European national development banks and Ukraine’s recent reforms, a Ukrainian Development Bank could integrate existing financial structures, channel EU aid, support small and medium-sized enterprises, and drive economic modernisation. Balancing local ownership with robust governance and civil oversight to mitigate corruption risks will be crucial to ensure effective integration into the EU and sustainable development
A Two-Timescale Decision-Hazard-Decision Formulation for Storage Usage Values Calculation
No full textThe penetration of renewable energies requires additional storages to deal with intermittency. Accordingly, there is growing interest in evaluating the opportunity cost (usage value) associated with stored energy in large storages, a cost obtained by solving a multistage stochastic optimization problem. Today, to compute usage values under uncertainties, an adequacy resource problem is solved using stochastic dynamic programming assuming a hazard-decision information structure. This modelling assumes complete knowledge of the coming week uncertainties, which is not adapted to the system operation as the intermittency occurs at smaller timescale. We equip the twotimescale problem with a new information structure considering planning and recourse decisions: decision-hazard-decision. This structure is used to decompose the multistage decision-making process into a nonanticipative planning step in which the on/off decisions for the thermal units are made, and a recourse step in which the power modulation decisions are made once the uncertainties have been disclosed. In a numerical case, we illustrate how usage values are sensitive as how the disclosure of information is modelled
Aeolus 2.0's thermal rotating shallow water model: A new paradigm for simulating extreme heatwaves, westerly jet intensification, and more
No full textInternational audienceIn this study, we demonstrate the dynamical core and applicability of Aeolus 2.0, a moist-convective thermal rotating shallow water model of intermediate complexity, along with its novel bulk aerodynamic and moist-convective schemes, in capturing the effects of increased radiative forcing on zonal winds and heatwaves. Simulations reveal seasonal patterns in zonal wind, temperature, and energy anomalies under increased radiative forcing during the summer solstice, winter solstice, and equinoxes. Increased radiative forcing enhances mid-latitudinal temperatures during the summer solstice in the Northern Hemisphere and the winter solstice in the Southern Hemisphere, leading to increased zonal wind velocity in the affected hemisphere, especially in the subtropics, while decreasing it in the opposite hemisphere. This thermal forcing also reduces the zonal wind velocity of polar cyclones in the hemisphere experiencing increased radiative forcing. During the autumn equinox, zonal wind velocity diminishes in the Southern Hemisphere, while a similar reduction occurs in the Northern Hemisphere during the spring equinox. Heightened meridional gradients significantly influence the poleward displacement of atmospheric circulation, particularly during the summer (northward) and winter (southward) solstices. Poleward eddy heat fluxes persist across hemispheres, indicating a consistent response to external heating. Increased radiative forcing during the summer and winter solstices amplifies prolonged heatwaves across land and ocean, exceeding impacts observed during the spring and autumn equinoxes
On non-negative solutions of stochastic Volterra equations with jumps and non-Lipschitz coefficients
No full textInternational audienceWe consider one-dimensional stochastic Volterra equations with jumps for which we establish conditions upon the convolution kernel and coefficients for the strong existence and pathwise uniqueness of a non-negative c\`adl\`ag solution. By using the approach recently developed in arXiv:2302.07758, we show the strong existence by using a nonnegative approximation of the equation whose convergence is proved via a variant of the Yamada--Watanabe approximation technique. We apply our results to L\'evy-driven stochastic Volterra equations. In particular, we are able to define a Volterra extension of the so-called alpha-stable Cox--Ingersoll--Ross process, which is especially used for applications in Mathematical Finance
From IoT Networks Deployment to Robust Location-based Services using the Digital Twin of a Building
No full textInternational audienceAlthough Building Information Modeling (BIM) has been around for over five decades, its integration with Big Data generated by IoT networks has raised research interest. This fusion enables the Digital Twin of a Building (DTB), a real-time virtual replica facilitating efficient location-based services, precise monitoring, and enhanced operational efficiency. Despite its alignment with the Smart City paradigm, widespread adoption is hindered by the initial investment for IoT network deployment. This article presents a comprehensive process, from optimizing IoT network deployment to implementing robust location-based services. A genetic algorithm leveraging the BIM database improves coverage by 44% compared to random deployments, while a multi-tier architecture based on deployed and roaming users’ devices extends service availability to 80% of devices without internet access, enhancing overall service quality by ∼200%. Eventually, the versatility of DTB is showcased through the use case of indoor guidance services, concluding with potential research directions using the DTB
Turbulence in the tropical stratosphere, equatorial Kelvin waves, and the quasi-biennial oscillation
No full textInternational audienceThe tropical stratosphere is the gateway to the global stratosphere and a commonly proposed location for solar geoengineering. The dynamics of this remote and difficult to observe region are poorly understood, particularly at turbulent length scales. Existing observational estimates of turbulence frequency and strength vary widely. Furthermore, the sources of turbulence and the relationship between turbulence and the mean flow are largely unknown. We assembled a 21-y database of high vertical resolution (10 m) radiosonde data from four equatorial sites in two ocean basins to study tropical stratospheric turbulence frequency, variability, and sources. Turbulent layers thicker than 200 m are identified using subcritical Richardson number as a proxy for turbulence. We show that the turbulent fraction of the tropical stratosphere is strongly modulated by the quasi-biennial oscillation (QBO). Turbulence is enhanced during the QBO phase shifts, and the atmosphere is most turbulent right before the QBO phase switches from negative to positive, where turbulent instabilities typically occur within specific phases of Kelvin waves. Turbulence is less common when the QBO phase is well established, and the atmosphere is least turbulent during the negative phase of the QBO. The turbulent fraction of the equatorial lower stratosphere varies over a factor of ten depending on QBO phase. This relationship provides a robust observational constraint on the multiscale dynamics within this region, which is useful for evaluating atmospheric models, studying wave-mean flow interactions in the context of the QBO, and informing the operation of stratospheric aircraft and the injection of aerosol for geoengineering
Log-normal Mutations and their Use in Detecting Surreptitious Fake Images
No full textInternational audienceIn many cases, adversarial attacks against fake detectors employ algorithms specifically crafted for automatic image classifiers. These algorithms perform well, thanks to an excellent ad hoc distribution of initial attacks. However, these attacks are easily detected due to their specific initial distribution. Consequently, we explore alternative black-box attacks inspired by generic black-box optimization tools, particularly focusing on the log-normal algorithm that we successfully extend to attack fake detectors. Moreover, we demonstrate that this attack evades detection by neural networks trained to flag classical adversarial examples. Therefore, we train more general models capable of identifying a broader spectrum of attacks, including classical black-box attacks designed for images, black-box attacks driven by classical optimization, and no-box attacks. By integrating these attack detection capabilities with fake detectors, we develop more robust and effective fake detection systems
Co-benefits of nature-based solutions exceed the costs of implementation
No full textInternational audienceNature-based solutions offer multiple benefits for ecosystems and societies, supporting their inclusion in policy and practice. This study contributes to closing the gap in quantifying the multiple outcomes of nature-based solutions by assessing 83 nature-based solutions in the Alps. We assessed biodiversity co-benefits and the monetary value of four ecosystem services (heatwave mitigation, flood regulation, climate regulation, and landslide protection) provided by these nature-based solutions to their respective beneficiaries. Forest nature-based solutions showed high values for the four ecosystem services, river and wetland nature-based solutions showed high values for biodiversity, and urban nature-based solutions contributed a lower biodiversity value but were highly cost effective, benefiting a larger population. We estimated a 2.8:1 return on investment benefiting a total of 91,324 persons. We highlight the need for integrating biodiversity and multiple ecosystem services for future nature-based solutions funding and implementation, together with their role to mitigate and adapt to climate change
Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals
No full textInternational audienceIn this article, we derive fully guaranteed error bounds for the energy of convex nonlinear mean-field models. These results apply in particular to Kohn-Sham equations with convex density functionals, which includes the reduced Hartree-Fock (rHF) model, as well as the Kohn-Sham model with exact exchange-density functional (which is unfortunately not explicit and therefore not usable in practice). We then decompose the obtained bounds into two parts, one depending on the chosen discretization and one depending on the number of iterations performed in the self-consistent algorithm used to solve the nonlinear eigenvalue problem, paving the way for adaptive refinement strategies. The accuracy of the bounds is demonstrated on a series of test cases, including a Silicon crystal and an Hydrogen Fluoride molecule simulated with the rHF model and discretized with planewaves. We also show that, although not anymore guaranteed, the error bounds remain very accurate for a Silicon crystal simulated with the Kohn-Sham model using nonconvex exchangecorrelation functionals of practical interest