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We have conducted a series of scattering experiments at the uranium M4 absorption edge on low-symmetry uranium compounds (U2N3 and U3O8) produced as epitaxial films. At weak and forbidden reflections, we find a resonant signal, independent of temperature, with an energy dependence resembling the imaginary part of the scattering factor. Theory, using the FDMNES code, shows that these results can be reliably reproduced assuming that they originate from aspherical 5f electron charge distributions around the U nucleus. Such effects arise from the intrinsic anisotropy of the 5f shell and from the mixing of the 5f electrons of uranium with the outer 2p electrons of the anions. The good agreement between theory and experiment includes azimuthal scattering dependencies, as well as polarization states of the scattered photons. The methodology reported here opens the way for a deeper understanding of the role of the 5f electrons in the bonding in actinide compounds., Comment: Submitted to Physical Review B

The two-layer quasi-geostrophic equations (2QGE) is a simplified model that describes the dynamics of a stratified, wind-driven ocean in terms of potential vorticity and stream function. Its numerical simulation is plagued by a high computational cost due to the size of the typical computational domain and the need for high resolution to capture the full spectrum of turbulent scales. In this paper, we present a data-driven reduced order model (ROM) for the 2QGE that drastically reduces the computational time to predict ocean dynamics, especially when there are variable physical parameters. The main building blocks of our ROM are: i) proper orthogonal decomposition (POD) and ii) long short-term memory (LSTM) recurrent neural networks. Snapshots data are collected from a high-resolution simulation for part of the time interval of interest and for given parameter values in the case of variable parameters. POD is applied to each field variable to extract the dominant modes and a LSTM model is trained on the modal coefficients associated with the snapshots for each variable. Then, the trained LSTM models predict the modal coefficients for the remaining part of the time interval of interest and for a new parameter value. To illustrate the predictive performance of our POD-LSTM ROM and the corresponding time savings, we consider an extension of the so-called double-gyre wind forcing test. We show that the POD-LSTM ROM is accurate in predicting both time-averaged fields and time-dependent quantities (modal coefficients, enstrophy, and kinetic energy), even when retaining only 10-20\% of the singular value energy of the system. The computational speed up for the prediction is about up to 1E+07 compared to a finite volume based full order method., Comment: 41 pages, 23 figures

We consider an autonomous reconnaissance mission where a drone has to visit several points of interest and communicate the intel back to the base. At every point of interest, the drone has the option to either send back all available info, or continue to the next point of interest and communicate at a later stage. Both choices have a chance of detection, meaning the mission fails. We wish to maximize the expected amount of information gathered by the mission. This is modeled by a routing problem in a weighted graph. We discuss the ILP formulation of this problem, show it is NP-complete, and use a genetic algorithm to find good solutions for up to ten points of interest., Comment: 26 pages, 5 figures

We prove an analog of the Deligne conjecture for prestacks. We show that given a prestack $\mathbb A$, its Gerstenhaber--Schack complex $\mathbf{C}_{\mathsf{GS}}(\mathbb A)$ is naturally an $E_2$-algebra. This structure generalises both the known $\mathsf{L}_\infty$-algebra structure on $\mathbf{C}_{\mathsf{GS}}(\mathbb A)$, as well as the Gerstenhaber algebra structure on its cohomology $\mathbf{H}_{\mathsf{GS}}(\mathbb A)$. The main ingredient is the proof of a conjecture of Hawkins \cite{hawkins}, stating that the homology of the dg operad $\mathsf{Quilt}$ has vanishing homology in positive degrees. As a corollary, $\Quilt$ is quasi-isomorphic to the operad $\mathsf{Brace}$ encoding brace algebras. In addition, we improve the $L_\infty$-structure on $\Quilt$ be showing that it originates from a $\mathsf{PreLie}_\infty$-structure lifting the $\mathsf{PreLie}$-structure on $\mathsf{Brace}$ in homology., Comment: Comments are welcome

Modern railway traction systems are often equipped with anti-slip control strategies to comply with performance and safety requirements. A certain amount of slip is needed to increase the torque transferred by the traction motors onto the rail. Commonly, constant slip control is used to limit the slip velocity between the wheel and rail avoiding excessive slippage and vehicle derailment. This is at the price of not fully utilizing the train's traction and braking capabilities. Finding the slip at which maximum traction force occurs is challenging due to the non-linear relationship between slip and wheel-rail adhesion coefficient, as well as to its dependence on rail and wheel conditions. Perturb and observe (P\&O) and steepest gradient (SG) methods have been reported for the Maximum Adhesion Tracking (MAT) search. However, both methods exhibit weaknesses. Two new MAT strategies are proposed in this paper which overcome the limitations of existing methods, using Fuzzy Logic Controller (FLC) and Particle Swarm Optimization (PSO) respectively. Existing and proposed methods are first simulated and further validated experimentally using a scaled roller rig under identical conditions. The results show that the proposed methods improve the traction capability with lower searching time and oscillations compared to existing solutions. Tuning complexity and computational requirements will also be shown to be favorable to the proposed methods., Comment: 16 pages, 21 figures

Ransomware has become one of the most widespread threats, primarily due to its easy deployment and the accessibility to services that enable attackers to raise and obfuscate funds. This latter aspect has been significantly enhanced with the advent of cryptocurrencies, which, by fostering decentralisation and anonymity, have transformed this threat into a large-scale outbreak. However, recent reports indicate that a small group of individuals dominate the ransomware ecosystem and try to obfuscate their activity using multiple strains characterised by a short time to live. This scenario suggests that different strains could share mechanisms in ransom collection, fund movement, and money laundering operations. For this reason, this study aims to analyse the address-transaction graphs generated in the Bitcoin network by low-labelled ransomware families. Our goals are to identify payment spreading patterns for evaluating the evolution of ransomware families and to detect similarities among different strains that potentially can be controlled by the same attacker. Specifically, this latter task assigns an address behaviour to each node in the address-transaction graphs according to its dynamics. The distribution of the behaviours in each strain is finally used to evaluate the closeness among different ransomware families. Our findings show that although ransomware families can quickly establish connections with millions of addresses, numerous families require multiple-step analysis. Furthermore, the study demonstrates that the introduced behaviours can effectively be used to highlight similarities among different ransomware strains. The outcome shows that families are similar primarily due to behaviours usually associated with ransom collection and money laundering operations.+, Comment: Presented and Published at The 7th International Conference on Blockchain (Blockchain 2024)

We study the asymptotic behaviour of the cohomology of subgroups $\Gamma$ of an algebraic group $G$ with coefficients in the various irreducible rational representations of $G$ and raise a conjecture about it. Namely, we expect that the dimensions of these cohomology groups approximate the $\ell^2$-Betti numbers of $\Gamma$ with a controlled error term. We provide positive answers when $G$ is a product of copies of $SL_2$. As an application, we obtain new proofs of J. Lott's and W. L\"uck's computation of the $\ell^2$-Betti numbers of hyperbolic $3$-manifolds and W. Fu's upper bound on the growth of cusp forms for non totally real fields, which is sharp in the imaginary quadratic case., Comment: 33 pages, comments are welcome!

We show how fermionic statistics can be naturally incorporated in tensor networks on arbitrary graphs through the use of graded Hilbert spaces. This formalism allows to use tensor network methods for fermionic lattice systems in a local way, avoiding the need of a Jordan-Wigner transformation or the explicit tracking of leg crossings by swap gates in 2D tensor networks. The graded Hilbert spaces can be readily integrated with other internal and lattice symmetries in tensor networks, and only require minor extensions to an existing tensor network software package. We review and benchmark the fermionic versions of common algorithms for matrix product states and projected entangled-pair states., Comment: 73 pages, 6 figures

Although the two-layer quasi-geostrophic equations (2QGE) are a simplified model for the dynamics of a stratified, wind-driven ocean, their numerical simulation is still plagued by the need for high resolution to capture the full spectrum of turbulent scales. Since such high resolution would lead to unreasonable computational times, it is typical to resort to coarse low-resolution meshes combined with the so-called eddy viscosity parameterization to account for the diffusion mechanisms that are not captured due to mesh under-resolution. We propose to enable the use of further coarsened meshes by adding a (linear or nonlinear) differential low-pass to the 2QGE, without changing the eddy viscosity coefficient. While the linear filter introduces constant (additional) artificial viscosity everywhere in the domain, the nonlinear filter relies on an indicator function to determine where and how much artificial viscosity is needed. Through several numerical results for a double-gyre wind forcing benchmark, we show that with the nonlinear filter we obtain accurate results with very coarse meshes, thereby drastically reducing the computational time (speed up ranging from 30 to 300)., Comment: 34 pages, 13 figures

Tools for fighting cyber-criminal activities using new technologies are promoted and deployed every day. However, too often, they are unnecessarily complex and hard to use, requiring deep domain and technical knowledge. These characteristics often limit the engagement of law enforcement and end-users in these technologies that, despite their potential, remain misunderstood. For this reason, in this study, we describe our experience in combining learning and training methods and the potential benefits of gamification to enhance technology transfer and increase adult learning. In fact, in this case, participants are experienced practitioners in professions/industries that are exposed to terrorism financing (such as Law Enforcement Officers, Financial Investigation Officers, private investigators, etc.) We define training activities on different levels for increasing the exchange of information about new trends and criminal modus operandi among and within law enforcement agencies, intensifying cross-border cooperation and supporting efforts to combat and prevent terrorism funding activities. On the other hand, a game (hackathon) is designed to address realistic challenges related to the dark net, crypto assets, new payment systems and dark web marketplaces that could be used for terrorist activities. The entire methodology was evaluated using quizzes, contest results, and engagement metrics. In particular, training events show about 60% of participants complete the 11-week training course, while the Hackathon results, gathered in two pilot studies (Madrid and The Hague), show increasing expertise among the participants (progression in the achieved points on average). At the same time, more than 70% of participants positively evaluate the use of the gamification approach, and more than 85% of them consider the implemented Use Cases suitable for their investigations.

We introduce symplectic billiards for pairs of possibly non-convex polygons. After establishing basic properties, we give several criteria on pairs of polygons for the symplectic billiard map to be fully periodic, i.e. $\textit{every}$ orbit is periodic. First fully periodic examples were discovered by Albers-Tabachnikov [AT18] and Albers-Banhatti-Sadlo-Schwartz-Tabachnikov in [ABS+19]. Our criteria allow us to construct a plethora of new examples. Moreover, we provide an example of a pair of polygons where the symplectic billiard map is fully periodic while having orbits of arbitrarily large period. After giving a class of examples which provably have isolated periodic orbits (and are thus not fully periodic) we exhibit the first example without any periodic orbits at all. It is open whether being fully periodic with unbounded period or having no periodic orbits at all is possible in the single polygon setting. Finally, we prove that if one replaces polygons by smooth strictly convex curves then there are always infinitely many periodic orbits., Comment: 37 pages, 41 figures

This paper presents a Nonlinear Model Predictive Control (NMPC) scheme targeted at motion planning for mechatronic motion systems, such as drones and mobile platforms. NMPC-based motion planning typically requires low computation times to be able to provide control inputs at the required rate for system stability, disturbance rejection, and overall performance. Although there exist various ways in literature to reduce the solution times in NMPC, such times may not be low enough to allow real-time implementations. This paper presents ASAP-MPC, an approach to handle varying, sometimes restrictively large, solution times with an asynchronous update scheme, always allowing for full convergence and real-time execution. The NMPC algorithm is combined with a linear state feedback controller tracking the optimised trajectories for improved robustness against possible disturbances and plant-model mismatch. ASAP-MPC seamlessly merges trajectories, resulting from subsequent NMPC solutions, providing a smooth and continuous overall trajectory for the motion system. This frameworks applicability to embedded applications is shown on two different experiment setups where a state-of-the-art method fails: a quadcopter flying through a cluttered environment in hardware-in-the-loop simulation and a scale model truck-trailer manoeuvring in a structured lab environment., Comment: This work has been submitted to the IEEE for possible publication

Recently, Sharma et al. [Adv. Sci. 9, 2203473 (2022)] claimed that thin films (around 20 nm) of UO2 deposited on perovskite substrates exhibit strongly enhanced paramagnetism (called induced ferromagnetism by the authors). Moments of up to 3 Bohr magneton/U atom were claimed in magnetic fields of 6 T. We have reproduced such films and, after characterisation, have examined them with X-ray circular magnetic dichroism (XMCD) at the uranium M edges, a technique that is element specific. We do not confirm the published results. We find a small increase, as compared to the bulk, in the magnetic susceptibility of UO2 in such films, but the magnetisation versus field curves, measured by XMCD, are linear with field and there is no indication of any ferromagnetism. The absence of any anomaly around 30 K (the antiferromagnetic ordering temperature of bulk UO2) in the XMCD signal suggests the films do not order magnetically.

Prestacks are algebro-geometric objects whose defining relations are far from quadratic. Indeed, they are cubic and quartic, and moreover inhomogeneous. We show that box operads, a rectangular type of operads introduced in arXiv:2305.20036, constitute the correct framework to encode them and resolve their relations up to homotopy. Our first main result is a Koszul duality theory for box operads, extending the duality for (nonsymmetric) operads. In this new theory, the classical restriction of being quadratic is replaced by the notion of being $\textit{thin-quadratic}$, a condition referring to a particular class of ``thin'' operations. Our main case of interest is the box operad $Lax$ encoding lax prestacks as algebras. We show that $Lax$ is not Koszul by explicitly computing its Koszul complex. We then go on to remedy the situation by suitably restricting the Koszul dual box cooperad $Lax^{\antishriek}$ to obtain our second main result: we establish a minimal (in particular cofibrant) model $Lax_{\infty}$ for the box operad $Lax$ encoding lax prestacks. This sheds new light on Markl's question on the existence of a cofibrant model for the operad encoding presheaves of algebras from arXiv:math/0103052. Indeed, we answer the parallel question with presheaves viewed as prestacks, and prestacks considered as algebras over a box operad, in the positive., Comment: 45 pages, lots of pictures; All comments are welcome!

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 45 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations., Comment: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation

Despite the recent advances in pre-production bug detection, heap-use-after-free and heap-buffer-overflow bugs remain the primary problem for security, reliability, and developer productivity for applications written in C or C++, across all major software ecosystems. Memory-safe languages solve this problem when they are used, but the existing code bases consisting of billions of lines of C and C++ continue to grow, and we need additional bug detection mechanisms. This paper describes a family of tools that detect these two classes of memory-safety bugs, while running in production, at near-zero overhead. These tools combine page-granular guarded allocation and low-rate sampling. In other words, we added an "if" statement to a 36-year-old idea and made it work at scale. We describe the basic algorithm, several of its variants and implementations, and the results of multi-year deployments across mobile, desktop, and server applications.

Magnetar magnetospheres are strongly twisted, and are able to power sudden energetic events through the rapid release of stored electromagnetic energy. In this paper, we investigate twisted relativistic force-free axisymmetric magnetospheres of rotating neutron stars. We obtain numerical solutions of such configurations using the method of simultaneous relaxation for the magnetic field inside and outside the light-cylinder. We introduce a toroidal magnetic field in the region of closed field-lines that is associated with a poloidal electric current distribution in that region, and explore various mathematical expressions for that distribution. We find that, by increasing the twist, a larger fraction of magnetic field-lines crosses the light-cylinder and opens up to infinity, thus increasing the size of the polar caps and enhancing the spin-down rate. We also find that, for moderately to strongly twisted magnetospheres, the region of closed field-lines ends at some distance inside the light-cylinder. We discuss the implications of these solutions on the variation of magnetar spin-down rates, moding and nulling of pulsars, the relation between the angular shear and the twist and the overall shape of the magnetosphere., Comment: Accepted by MNRAS

Lightcurves of many classical novae deviate from the canonical "fast rise - smooth decline" pattern and display complex variability behavior. We present the first TESS-space-photometry-based investigation of this phenomenon. We use TESS Sector 41 full-frame images to extract a lightcurve of the slow Galactic nova V606 Vul that erupted nine days prior to the start of the TESS observations. The lightcurve covers the first of two major peaks of V606 Vul that was reached 19 days after the start of the eruption. The nova reached its brightest visual magnitude V=9.9 in its second peak 64 days after the eruption onset, following the completion of Sector 41 observations. To increase the confidence level of the extracted lightcurve, we performed the analysis using four different codes implementing the aperture photometry (Lightkurve, VaST) and image subtraction (TESSreduce, tequila_shots) and find good agreement between them. We performed ground-based photometric and spectroscopic monitoring to complement the TESS data. The TESS lightcurve reveals two features: periodic variations (0.12771d, 0.01mag average peak-to-peak amplitude) that disappeared when the source was within 1mag of peak optical brightness and a series of isolated mini-flares (with peak-to-peak amplitudes of up to 0.5mag) appearing at seemingly random times. We interpret the periodic variations as the result of azimuthal asymmetry of the photosphere engulfing the nova-hosting binary that was distorted by and rotating with the binary. Whereas we use spectra to associate the two major peaks in the nova lightcurve with distinct episodes of mass ejection, the origin of mini-flares remains elusive., Comment: 31 pages, 10 figures, submitted to ApJ; comments welcome

As organizations increasingly use cloud services to host their IT infrastructure, there is a need to share data among these cloud hosted services and systems. A majority of IT organizations have workloads spread across different cloud service providers, growing their multi-cloud environments. When an organization grows their multi-cloud environment, the threat vectors and vulnerabilities for their cloud systems and services grow as well. The increase in the number of attack vectors creates a challenge of how to prioritize mitigations and countermeasures to best defend a multi-cloud environment against attacks. Utilizing multiple industry standard risk analysis tools, we conducted an analysis of multi-cloud threat vectors enabling calculation and prioritization for the identified mitigations and countermeasures. The prioritizations from the analysis showed that authentication and architecture are the highest risk areas of threat vectors. Armed with this data, IT managers are able to more appropriately budget cybersecurity expenditure to implement the most impactful mitigations and countermeasures.

Thin layers of orthorhombic uranium ({\alpha}-U) have been grown onto buffered sapphire substrates by d.c. magnetron sputtering, resulting in the discovery of new epitaxial matches to Ti(00.1) and Zr(00.1) surfaces. These systems have been characterised by X-ray diffraction and reflectivity and the optimal deposition temperatures have been determined. More advanced structural characterisation of the known Nb(110) and W(110) buffered {\alpha}-U systems has also been carried out, showing that past reports of the domain structures of the U layers are incomplete. The ability of this low symmetry structure to form crystalline matches across a range of crystallographic templates highlights the complexity of U metal epitaxy and points naturally toward studies of the low temperature electronic properties of {\alpha}-U as a function of epitaxial strain.

Shrinking pattern dimensions leads to an increased variety of defect types in semiconductor devices. This has spurred innovation in patterning approaches such as Directed self-assembly (DSA) for which no traditional, automatic defect inspection software exists. Machine Learning-based SEM image analysis has become an increasingly popular research topic for defect inspection with supervised ML models often showing the best performance. However, little research has been done on obtaining a dataset with high-quality labels for these supervised models. In this work, we propose a method for obtaining coherent and complete labels for a dataset of hexagonal contact hole DSA patterns while requiring minimal quality control effort from a DSA expert. We show that YOLOv8, a state-of-the-art neural network, achieves defect detection precisions of more than 0.9 mAP on our final dataset which best reflects DSA expert defect labeling expectations. We discuss the strengths and limitations of our proposed labeling approach and suggest directions for future work in data-centric ML-based defect inspection., Comment: 8 pages, 10 figures, accepted for the 38th EMLC Conference 2023

Thin films based on silicon and transition-metal elements dominate the semiconducting industry and are ubiquitous in all modern devices. Films have also been produced in the rare-earth series of elements for both research and specialized applications. Thin films of uranium and uranium dioxide were fabricated in the 1960s and 1970s, but there was little sustained effort until the early 2000s. Significant programmes started at Oxford University (transferring to Bristol University in 2011), and Los Alamos National Laboratory (LANL) in New Mexico, USA. In this review we cover the work that has been published over the last ~20 years with these materials. Important breakthroughs occurred with the fabrication of epitaxial thin films of initially uranium metal and UO2, but more recently of many other uranium compounds and alloys. These have led to a number of different experiments that are reviewed, as well as some important trends. The interaction with the substrate leads to differing strain and hence changes in properties. An important advantage is that epitaxial films can often be made of materials that are impossible to produce as bulk single crystals. Examples are U3O8, U2N3 and alloys of U-Mo, which form in a modified bcc structure. Epitaxial films may also be used in applied research. They represent excellent surfaces, and it is at the surfaces that most of the important reactions occur in the nuclear fuel cycle. For example, the fuel-cladding interactions, and the dissolution of fuel by water in the long-term storage of spent fuel. To conclude, we discuss possible future prospects, examples include bilayers containing uranium for spintronics, and superlattices that could be used in heterostructures. Such applications will require a more detailed knowledge of the interface interactions in these systems, and this is an important direction for future research., Comment: 87 pages, 4 tables, 42 figures. Submitted to Advances in Physics

With the increasing use of multi-cloud environments, security professionals face challenges in configuration, management, and integration due to uneven security capabilities and features among providers. As a result, a fragmented approach toward security has been observed, leading to new attack vectors and potential vulnerabilities. Other research has focused on single-cloud platforms or specific applications of multi-cloud environments. Therefore, there is a need for a holistic security and vulnerability assessment and defense strategy that applies to multi-cloud platforms. We perform a risk and vulnerability analysis to identify attack vectors from software, hardware, and the network, as well as interoperability security issues in multi-cloud environments. Applying the STRIDE and DREAD threat modeling methods, we present an analysis of the ecosystem across six attack vectors: cloud architecture, APIs, authentication, automation, management differences, and cybersecurity legislation. We quantitatively determine and rank the threats in multi-cloud environments and suggest mitigation strategies., Comment: 27 pages, 9 figures