Bidding behaviour in the ECB’s main refinancing operations during the financial crisis

Liquidity provision through its repo auctions has been one of the main instruments of the European Central Bank (ECB) to address the recent tensions in financial markets since summer 2007. In this paper, we analyse banks’ bidding behaviour in the ECB’s main refinancing operations (MROs) during the ongoing turmoil in money and financial markets. We employ a unique data set comprising repo auctions from March 2004 to October 2008 with bidding data from 877 counterparties. We find that increased bid rates during the turmoil can be explained by, inter alia, the increased individual refinancing motive, the increased attractiveness of the ECB’s tender operations due to its collateral framework and banks’ bidding more aggressively, i.e. at higher rates to avoid being rationed at the marginal rate in times of increased liquidity uncertainty. JEL Classification: E52, D44, C33, C34Bidding Behavior, Central Bank Auctions, Financial Market Turmoil, monetary policy instruments, Panel Sample Selection Model

Index estimates for sequences of harmonic maps

In this paper we study upper and lower bounds of the index and the nullity for sequences of harmonic maps with uniformly bounded Dirichlet energy from a two-dimensional Riemann surface into a compact target manifold. The main difficulty stems from the fact that in the limit the sequence can develop finitely many bubbles. We obtain the index bounds by studying the limiting behavior of sequences of eigenfunctions of the linearized operator and the key novelty of the present paper is that we diagonalize the index form of the Dirichlet energy with respect to a bilinear form which varies with the sequence of harmonic maps and which helps us to show the convergence of the sequence of eigenfunctions on the weak limit, the bubbles and the intermediate neck regions. Finally, we sketch how to modify our arguments in order to also cover the more general case of sequences of critical points of two-dimensional conformally invariant variational problems.Comment: 20 page

Approximate locality for quantum systems on graphs

In this Letter we make progress on a longstanding open problem of Aaronson and Ambainis [Theory of Computing 1, 47 (2005)]: we show that if A is the adjacency matrix of a sufficiently sparse low-dimensional graph then the unitary operator e^{itA} can be approximated by a unitary operator U(t) whose sparsity pattern is exactly that of a low-dimensional graph which gets more dense as |t| increases. Secondly, we show that if U is a sparse unitary operator with a gap \Delta in its spectrum, then there exists an approximate logarithm H of U which is also sparse. The sparsity pattern of H gets more dense as 1/\Delta increases. These two results can be interpreted as a way to convert between local continuous-time and local discrete-time processes. As an example we show that the discrete-time coined quantum walk can be realised as an approximately local continuous-time quantum walk. Finally, we use our construction to provide a definition for a fractional quantum fourier transform.Comment: 5 pages, 2 figures, corrected typ

causalgraph: A Python Package for Modeling, Persisting and Visualizing Causal Graphs Embedded in Knowledge Graphs

This paper describes a novel Python package, named causalgraph, for modeling and saving causal graphs embedded in knowledge graphs. The package has been designed to provide an interface between causal disciplines such as causal discovery and causal inference. With this package, users can create and save causal graphs and export the generated graphs for use in other graph-based packages. The main advantage of the proposed package is its ability to facilitate the linking of additional information and metadata to causal structures. In addition, the package offers a variety of functions for graph modeling and plotting, such as editing, adding, and deleting nodes and edges. It is also compatible with widely used graph data science libraries such as NetworkX and Tigramite and incorporates a specially developed causalgraph ontology in the background. This paper provides an overview of the package's main features, functionality, and usage examples, enabling the reader to use the package effectively in practice

Soiling determination for parabolic trough collectors based on operational data analysis and machine learning

Advanced cleaning strategies for parabolic trough collectors at concentrated solar power plants maximize the yield and minimize the costs for cleaning activities. However, they require information about the current soiling level of each collector. In this work, a novel, data-driven method for soiling estimation with machine learning for parabolic trough collectors is developed using gloss values as a surrogate for soiling values. Operational data and meteorological data from the solar field Andasol-3 with changing time horizons are used together with various Machine Learning techniques to estimate the soiling of every collector in the field. The best results were achieved with a Decision Tree model, with a coefficient of determination of $^2$ = 0.77 from the maximum value of 1 and a mean squared error of = 6.14 for the determination of specific soiling values. A second metric to evaluate the quality of soiling predictions from the models classifies whether soiling is above or below a cleaning threshold was also investigated. Model results are compared to soiling measurements that indicate the need for cleanings. Cleaning recommendations are derived and compared with the current fixed-time cleaning schedule of Andasol-3. All models show an improvement over the cleaning schedule currently in use. The use of a Decision Tree model increases the detected necessary cleanings by 12.2 %, while the number of unnecessary cleanings are reduced by 14.3 %. This has the potential to reduce operational costs and increase the solar field yield. The dataset used in this work is made publicly available https://doi.org/10.5281/zenodo.7061913, along with the code to reproduce all results, which can be found at https://doi.org/10.5281/zenodo.7554806

Aviator: a web service for monitoring the availability of web services

With Aviator, we present a web service and repository that facilitates surveillance of online tools. Aviator consists of a user-friendly website and two modules, a literature-mining based general and a manually curated module. The general module currently checks 9417 websites twice a day with respect to their availability and stores many features (frontend and backend response time, required RAM and size of the web page, security certificates, analytic tools and trackers embedded in the webpage and others) in a data warehouse. Aviator is also equipped with an analysis functionality, for example authors can check and evaluate the availability of their own tools or those of their peers. Likewise, users can check the availability of a certain tool they intend to use in research or teaching to avoid including unstable tools. The curated section of Aviator offers additional services. We provide API snippets for common programming languages (Perl, PHP, Python, JavaScript) as well as an OpenAPI documentation for embedding in the backend of own web services for an automatic test of their function. We query the respective APIs twice a day and send automated notifications in case of an unexpected result. Naturally, the same analysis functionality as for the literature-based module is available for the curated section. Aviator can freely be used at https://www.ccb.uni-saarland.de/aviator

Additively manufactured AlSi10Mg lattices – Potential and limits of modelling as-designed structures

Additive manufacturing overcomes the restrictions of classical manufacturing methods and enables the production of near-net-shaped, complex geometries. In that context, lattice structures are of high interest due to their superior weight reduction potential. AlSi10Mg is a well-known alloy for additive manufacturing and well suited for such applications due to its high strength to material density ratio. It has been selected in this study for producing bulk material and complex geometries of a strut-based lattice type (rhombic dodecahedron). A detailed characterisation of as-built and heat-treated specimens has been conducted including microstructural analyses, identification of imperfections and rigorous mechanical testing under different load conditions. An isotropic elastic–plastic material model is deduced on the basis of tension test results of bulk material test specimens. Performed experiments under compression, shear, torsion and tension load are compared to their virtual equivalents. With the help of numerical modelling, the overall structural behaviour was simulated using the detailed lattice geometry and was successfully predicted by the presented numerical models. The discussion of the limits of this approach aims to evaluate the potential of the numerical assessment in the modelling of the properties for novel lightweight structures

miEAA 2023: updates, new functional microRNA sets and improved enrichment visualizations

MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in regulating diverse biological processes. Extracting functional insights from a list of miRNAs is challenging, as each miRNA can potentially interact with hundreds of genes. To address this challenge, we developed miEAA, a flexible and comprehensive miRNA enrichment analysis tool based on direct and indirect miRNA annotation. The latest release of miEAA includes a data warehouse of 19 miRNA repositories, covering 10 different organisms and 139 399 functional categories. We have added information on the cellular context of miRNAs, isomiRs, and high-confidence miRNAs to improve the accuracy of the results. We have also improved the representation of aggregated results, including interactive Upset plots to aid users in understanding the interaction among enriched terms or categories. Finally, we demonstrate the functionality of miEAA in the context of ageing and highlight the importance of carefully considering the miRNA input list. MiEAA is free to use and publicly available at https://www.ccb.uni-saarland.de/mieaa/