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Understanding the complex ground state of van der Waals (vdW) magnets is essential for designing new materials and devices that leverage these platforms. Here, we investigate a two-dimensional vdW ferromagnet -- Fe$_5$GeTe$_2$-- with one of the highest reported Curie temperatures, to elucidate its magnetic excitations and charge order. Using Fe $L_3 - $edge resonant inelastic x-ray scattering, we find the dual character of magnetic excitations, consisting of a coherent magnon and a continuum, similar to what is reported for its sister compound Fe$_3$GeTe$_2$. The magnon has an energy of $\approx$ 36 meV at the maximum in-plane momentum transfer ($-$0.35 r.l.u.) allowed at Fe $L_3 - $edge. A broad and non-dispersive continuum extends up to 150 meV, 50$\%$ higher energy than in Fe$_3$GeTe$_2$. Its intensity is sinusoidally modulated along the $L$ direction, with a period matching the inter-slab distance. Our findings suggest that while the unconventional dual character of magnetic excitations is generic to ternary Fe-Ge-Te vdW magnets, the correlation length of the out-of-plane magnetic interaction increases in Fe$_5$GeTe$_2$ as compared to Fe$_3$GeTe$_2$, supporting a stronger three-dimensional character for the former. Furthermore, by investigating the $\pm$(1/3, 1/3, $L$) peaks by resonant x-ray diffraction, we conclude these to have structural origin rather than charge order -- as previously reported -- and suggest doubling of the structural unit cell along the $c-$axis., Comment: 17 pages, 3 figures

Superconductivity in infinite layer nickelates Nd1-xSrxNiO2 has so far been achieved only in thin films raising questions on the role of substrates and interfaces. Given the challenges associated with their synthesis it is imperative to identify their intrinsic properties. We use Resonant Inelastic X-ray Scattering (RIXS) to investigate the influence of the SrTiO3 capping layer on the excitations of Nd1-xSrxNiO2 (x = 0 and 0.2). Spin excitations are observed in parent and 20% doped Nd1-xSrxNiO2 regardless of capping, proving that magnetism is intrinsic to infinite-layer nickelates and appears in a significant fraction of their phase diagram. In parent and superconducting Nd1-xSrxNiO2, the spin excitations are slightly hardened in capped samples compared to the non-capped ones. Additionally, a weaker Ni - Nd charge transfer peak at ~ 0.6 eV suggests that the hybridization between Ni 3d and Nd 5d orbitals is reduced in capped samples. From our data, capping induces only minimal differences in Nd1-xSrxNiO2 and we phenomenologically discuss these differences based on the reconstruction of the SrTiO3 - NdNiO2 interface and other mechanisms such as crystalline disorder., Comment: 9 pages, 6 figures

Asgard/NOTT is an ERC-funded project hosted at KU Leuven and is part of a new visitor instrumental suite, called Asgard, under preparation for the Very Large Telescope Interferometer (VLTI). Leveraging nulling capabilities and the long VLTI baselines, it is optimized for high-contrast imaging of the snow line region around young nearby main-sequence stars. This will enable the characterization of the atmosphere of young giant exoplanets and warm/hot exozodiacal dust with spectroscopy in the L'-band (3.5-4.0$\mu$m). In this work, we present the first lab assembly of the instrument done at KU Leuven and the technical solutions to tackle the challenge of performing nulling in the mid-infrared despite the thermal background. The opto-mechanical design of the warm optics and the injection system for the photonic chip are described. The alignment procedure used to assemble the system is also presented. Finally, the first experimental results, including fringes and null measurements, are given and confirm the adequacy of the bench to test and optimize the Asgard/NOTT instrument., Comment: 13 pages (incl. 14 figures); Proc. SPIE Astronomical Telescopes + Instrumentation 2024 (Yokohama; Japan), Optical and Infrared Interferometry and Imaging IX

ESO's Very Large Telescope Interferometer has a history of record-breaking discoveries in astrophysics and significant advances in instrumentation. The next leap forward is its new visitor instrument, called Asgard. It comprises four natively collaborating instruments: HEIMDALLR, an instrument performing both fringe tracking and stellar interferometry simultaneously with the same optics, operating in the K band; Baldr, a Strehl optimizer in the H band; BIFROST, a spectroscopic combiner to study the formation processes and properties of stellar and planetary systems in the Y-J-H bands; and NOTT, a nulling interferometer dedicated to imaging nearby young planetary systems in the L band. The suite is in its integration phase in Europe and should be shipped to Paranal in 2025. In this article, we present details of the alignment and calibration unit, the observing modes, the integration plan, the software architecture, and the roadmap to completion of the project.

NOTT (formerly Hi-5) is the L'-band (3.5-4.0~microns) nulling interferometer of Asgard, an instrument suite in preparation for the VLTI visitor focus. The primary scientific objectives of NOTT include characterizing (i) young planetary systems near the snow line, a critical region for giant planet formation, and (ii) nearby main-sequence stars close to the habitable zone, with a focus on detecting exozodiacal dust that could obscure Earth-like planets. In 2023-2024, the final warm optics have been procured and assembled in a new laboratory at KU Leuven. First fringes and null measurements were obtained using a Gallium Lanthanum Sulfide (GLS) photonic chip that was also tested at cryogenic temperatures. In this paper, we present an overall update of the NOTT project with a particular focus on the cold mechanical design, the first results in the laboratory with the final NOTT warm optics, and the ongoing Asgard integration activities. We also report on other ongoing activities such as the characterization of the photonic chip (GLS, LiNbO3, SiO), the development of the exoplanet science case, the design of the dispersion control module, and the progress with the self-calibration data reduction software., Comment: 11 pages (incl. 5 figures); Proc. SPIE Astronomical Telescopes + Instrumentation 2024 (Yokohama; Japan), Optical and Infrared Interferometry and Imaging VI

Segregation encodes information about society, such as social cohesion, mixing, and inequality. However, most past and current studies tackled socioeconomic (SE) segregation by analyzing static aggregated mobility networks, often without considering further individual features beyond income and, most importantly, without distinguishing individual-level from location-based income. Accessing individual-level income may help mapping macroscopic behavior into more granular mobility patterns, hence impacting segregation estimates. Here we combine a mobile phone dataset of daily mobility flows across Spanish districts stratified and adjusted by age, gender and income with census data of districts median income. We build mobility-based SE assortativity matrices for multiple demographics and observe mobility patterns of three income groups with respect to location-based SE classes. We find that SE assortativity differs when isolating the mobility of specific income groups: we observe that groups prefer to visit areas with higher average income than their own, which we call preferential mobility. Our analysis suggests substantial differences between weekdays and weekends SE assortativity by age class, with weekends characterized by higher SE assortativity. Our modeling approach shows that the radiation model, which typically performs best at reproducing inter-municipal population mobility, best fits middle income and middle-aged flows, while performing worse on young and low income groups. Our double-sided approach, focusing on assortativity patterns and mobility modeling, suggests that state of the art mobility models fail at capturing preferential mobility behavior. Overall, our work indicates that mobility models considering the interplay of SE preferential behavior, age and gender gaps may sensibly improve the state of the art models performance., Comment: 11 pages, 3 figures, complexity72h

The COVID19 pandemic highlighted the importance of non-traditional data sources, such as mobile phone data, to inform effective public health interventions and monitor adherence to such measures. Previous studies showed how socioeconomic characteristics shaped population response during restrictions and how repeated interventions eroded adherence over time. Less is known about how different population strata changed their response to repeated interventions and how this impacted the resulting mobility network. We study population response during the first and second infection waves of the COVID-19 pandemic in Chile and Spain. Via spatial lag and regression models, we investigate the adherence to mobility interventions at the municipality level in Chile, highlighting the significant role of wealth, labor structure, COVID-19 incidence, and network metrics characterizing business-as-usual municipality connectivity in shaping mobility changes during the two waves. We assess network structural similarities in the two periods by defining mobility hotspots and traveling probabilities in the two countries. As a proof of concept, we simulate and compare outcomes of an epidemic diffusion occurring in the two waves. Our analysis reveals the resilience of the mobility network across waves. We test the robustness of our findings recovering similar results for Spain. Finally, epidemic modeling suggests that historical mobility data from past waves can be leveraged to inform future disease spatial invasion models in repeated interventions. This study highlights the value of historical mobile phone data for building pandemic preparedness and lessens the need for real-time data streams for risk assessment and outbreak response. Our work provides valuable insights into the complex interplay of factors driving mobility across repeated interventions, aiding in developing targeted mitigation strategies.

The real estate market shows an inherent connection to space. Real estate agencies unevenly operate and specialize across space, price and type of properties, thereby segmenting the market into submarkets. We introduce here a methodology based on multipartite networks to detect the spatial segmentation emerging from data on housing online listings. Considering the spatial information of the listings, we build a bipartite network that connects agencies and spatial units. This bipartite network is projected into a network of spatial units, whose connections account for similarities in the agency ecosystem. We then apply clustering methods to this network to segment markets into spatially-coherent regions, which are found to be robust across different clustering detection algorithms, discretization of space and spatial scales, and across countries with case studies in France and Spain. This methodology addresses the long-standing issue of housing market segmentation, relevant in disciplines such as urban studies and spatial economics, and with implications for policymaking., Comment: 9 pages, 10 figures

Traditional notions of production function do not consider the time dimension, appearing thus timeless and instantaneous. We propose an agent-based model accounting for the whole production side of the economy to unfold the production process from its very beginning, when firms receive production orders, to the delivery of the products to the market. In the model we analyze with a high-degree of details how heterogeneous firms, having labor and capital as productive factors, behave along all the realization processes of their outputs. The main focus covers: i) the heterogeneous duration of firms' production processes, ii) the adaptive strategies they implement to adjust their choices, and iii) the possible failures which may occur due to the duration of the production. Our agent-based model is a controlled experiment: we use a virtual central planner mechanism, which acts as the demand side of the economy, to observe which firm individual behaviors and aggregate macroeconomic outcomes emerge as a reply to its different behaviors in a ceteris paribus environment. Our applied goal, then, is to discuss the role of industrial policy by modeling production processes in detail., Comment: 31 pages, 25 figures

Asgard/NOTT (previously Hi-5) is a European Research Council (ERC)-funded project hosted at KU Leuven and a new visitor instrument for the Very Large Telescope Interferometer (VLTI). Its primary goal is to image the snow line region around young stars using nulling interferometry in the L-band (3.5 to 4.0)$\mu$m, where the contrast between exoplanets and their host stars is advantageous. The breakthrough is the use of a photonic beam combiner, which only recently allowed the required theoretical raw contrast of $10^{-3}$ in this spectral range. Nulling interferometry observations of exoplanets also require a high degree of balancing between the four pupils of the VLTI in terms of intensity, phase, and polarization. The injection into the beam combiner and the requirements of nulling interferometry are driving the design of the warm optics and the injection system. The optical design up to the beam combiner is presented. It offers a technical solution to efficiently couple the light from the VLTI into the beam combiner. During the coupling, the objective is to limit throughput losses to 5% of the best expected efficiency for the injection. To achieve this, a list of different loss sources is considered with their respective impact on the injection efficiency. Solutions are also proposed to meet the requirements on beam balancing for intensity, phase, and polarization. The different properties of the design are listed, including the optics used, their alignment and tolerances, and their impact on the instrumental performances in terms of throughput and null depth. The performance evaluation gives an expected throughput loss of less than <6.4% of the best efficiency for the injection and a null depth of $\sim2.10^{-3}$, mainly from optical path delay errors outside the scope of this work., Comment: Accepted for publication in JATIS. 23 pages, 11 figures, 8 tables

We investigate properties of the pseudo-Riemannian volume, entropy, and diameter for convex cocompact representations $\rho : \Gamma \to \mathrm{SO}(p,q+1)$ of closed $p$-manifold groups. In particular: We provide a uniform lower bound of the product entropy times volume that depends only on the geometry of the abstract group $\Gamma$. We prove that the entropy is bounded from above by $p-1$ with equality if and only if $\rho$ is conjugate to a representation inside ${\rm S}({\rm O}(p,1)\times{\rm O}(q))$, which answers affirmatively to a question of Glorieux and Monclair. Lastly, we prove finiteness and compactness results for groups admitting convex cocompact representations with bounded diameter., Comment: 29 pages. Comments are welcome! Main changes from v1: we improved the statement of Lemma 4.2; we rewrote the proof of Lemma 4.3 (we thank in particular Timoth\'e Lemistre for sharing with us his strategy of proof); we updated the acknowledgments

Trip flow between areas is a fundamental metric for human mobility research. Given its identification with travel demand and its relevance for transportation and urban planning, many models have been developed for its estimation. These models focus on flow intensity, disregarding the information provided by the local mobility orientation. A field-theoretic approach can overcome this issue and handling both intensity and direction at once. Here we propose a general vector-field representation starting from individuals' trajectories valid for any type of mobility. By introducing four models of spatial exploration, we show how individuals' elections determine the mesoscopic properties of the mobility field. Distance optimization in long displacements and random-like local exploration are necessary to reproduce empirical field features observed in Chinese logistic data and in New York City Foursquare check-ins. Our framework is an essential tool to capture hidden symmetries in mesoscopic urban mobility, it establishes a benchmark to test the validity of mobility models and opens the doors to the use of field theory in a wide spectrum of applications., Comment: 13 pages, 8 figures, Appendices

Recent works[1-3] reported evidence for charge density waves (CDWs) in infinite layer nickelates (112 structure) based on resonant diffraction at the Ni $L_3$ edge measured at fixed scattering angle. We have found that a measurement with fixed momentum transfer, rather than scattering angle, does not show a resonance effect. We have also observed that a nearby structural Bragg peak from the substrate appears due to third harmonic content of the incident beam, and spreads intensity down to the region of the attributed CDW order. This was further confirmed by testing a bare substrate. We suggest procedures to confirm an effective resonant enhancement of a diffraction peak.

This paper introduces a comprehensive and original database on West Nile virus (WNV) outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized bulletins published by the Italian National Institute of Health (ISS) to demonstrate the potential utilization of this data for the research community. Our aim is to establish a centralized open-access repository that facilitates analysis and monitoring of the disease. We have collected and curated data on the type of infected host, along with additional information whenever available, including the type of infection, age, and geographic details at different levels of spatial aggregation. By combining our data with other sources of information such as weather data, it becomes possible to assess potential relationships between WNV outbreaks and environmental factors. We strongly believe in supporting public oversight of government epidemic management, and we emphasize that open data plays a crucial role in generating reliable results by enabling greater transparency.

In this article, we single out representations of surface groups into $\mathsf{PSL}_d(\mathbb{C})$ which generalize the well-studied family of pleated surfaces into $\mathsf{PSL}_2(\mathbb{C})$. Our representations arise as sufficiently generic $\lambda$-Borel Anosov representations, which are representations that are Borel Anosov with respect to a maximal geodesic lamination $\lambda$. For fixed $\lambda$ and $d$, we provide a holomorphic parametrization of the space $\mathcal{R}(\lambda,d)$ of $(\lambda,d)$-pleated surfaces which extends both work of Bonahon for pleated surfaces and Bonahon and Dreyer for Hitchin representations., Comment: 125 pages, 14 figures. Comments are welcome!

Distributed ledger technologies, also known as blockchains for enterprises, promise to significantly reduce the high cost of automating multi-party business workflows. We argue that a programming language for writing such on-ledger logic should satisfy three desiderata: (1) Provide concepts to capture the legal rules that govern real-world business workflows. (2) Include simple means for specifying policies for access and authorization. (3) Support the composition of simple workflows into complex ones, even when the simple workflows have already been deployed. We present the open-source smart contract language Daml based on Haskell with strict evaluation. Daml achieves these desiderata by offering novel primitives for representing, accessing, and modifying data on the ledger, which are mimicking the primitives of today's legal systems. Robust access and authorization policies are specified as part of these primitives, and Daml's built-in authorization rules enable delegation, which is key for workflow composability. These properties make Daml well-suited for orchestrating business workflows across multiple, otherwise heterogeneous parties. Daml contracts run (1) on centralized ledgers backed by a database, (2) on distributed deployments with Byzantine fault tolerant consensus, and (3) on top of conventional blockchains, as a second layer via an atomic commit protocol.

Semantic segmentation is a crucial step to extract quantitative information from medical (and, specifically, radiological) images to aid the diagnostic process, clinical follow-up. and to generate biomarkers for clinical research. In recent years, machine learning algorithms have become the primary tool for this task. However, its real-world performance is heavily reliant on the comprehensiveness of training data. Dafne is the first decentralized, collaborative solution that implements continuously evolving deep learning models exploiting the collective knowledge of the users of the system. In the Dafne workflow, the result of each automated segmentation is refined by the user through an integrated interface, so that the new information is used to continuously expand the training pool via federated incremental learning. The models deployed through Dafne are able to improve their performance over time and to generalize to data types not seen in the training sets, thus becoming a viable and practical solution for real-life medical segmentation tasks., Comment: 10 pages (main body), 5 figures. Work partially presented at the 2021 RSNA conference and at the 2023 ISMRM conference In this new version: added author and change in the acknowledgment

We establish a link between the behavior of length functions on Teichm\"uller space and the geometry of certain anti de Sitter 3-manifolds. As an application, we give new purely anti de Sitter proofs of results of Teichm\"uller theory such as (strict) convexity of length functions along shear paths and geometric bounds on their second variation along earthquakes. Along the way, we provide shear-bend coordinates for Mess' anti de Sitter 3-manifolds., Comment: 39 pages. Comments are welcome!