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Previous studies on natural samples of pampaloite (AuSbTe) revealed the crystal structure of a potentially cleavable and/or exfoliable material, while studies on natural and synthetic montbrayite (Sb-containing Au$_2$Te$_3$) claimed various chemical compositions for this low symmetry compound. Few investigations of synthetic samples have been reported for both materials, leaving much of their chemical, thermal and electronic characteristics unknown. Here, we investigate the stability, electronic properties and synthesis of the gold antimony tellurides AuSbTe and Au$_{1.9}$Sb$_{0.46}$Te$_{2.64}$ (montbrayite). Differential thermal analysis and $\textit{in situ}$ powder x-ray diffraction revealed that AuSbTe is incongruently melting, while Au$_{1.9}$Sb$_{0.46}$Te$_{2.64}$ is congruently melting. Calculations of the band structures and four-point resistivity measurements showed that AuSbTe is a semiconductor and Au$_{1.9}$Sb$_{0.46}$Te$_{2.64}$ a metal. Various synthesis attempts confirmed the limited stable chemical composition of Au$_{1.9}$Sb$_{0.46}$Te$_{2.64}$, identified successful methods to synthesize both compounds, and highlighted the challenges associated with single crystal synthesis of AuSbTe., Comment: 12 pages, 13 figures

Collaborative data analysis between countries is crucial for enabling fast responses to increasingly multi-country disease outbreaks. Often, data early in outbreaks are of sensitive nature and subject to strict privacy restrictions. Thus, federated analysis, which implies decentralised collaborative analysis where no raw data sharing is required, emerged as a novel approach solving issues around data privacy and confidentiality. In the present study, we propose two approaches to federated analysis, based on simple Bayesian statistics and exploit this simplicity to make them feasible for rapid collaboration without the risks of data leaks and data reidentification, as they require neither data sharing nor direct communication between devices. The first approach uses summaries from parameters' posteriors previously obtained at a different location to update truncated normal distributions approximating priors of a new model. The second approach uses the entire previously sampled posterior, approximating via a multivariate normal distribution. We test these models on simulated and on real outbreak data to estimate the incubation period of infectious diseases. Results indicate that both approaches can recover incubation period parameters accurately, but they differ in terms of inferential capacity. The posterior summary approach shows higher stability and precision, but it cannot capture posterior correlations, meaning it is inferentially limited. The whole posterior approach can capture correlations, but it shows less stability, and its applicability is limited to fewer prior distributions. We discuss results in terms of the advantages of their simplicity and privacy-preserving properties, and in terms of their limited generalisability to more complex analytical models., Comment: submitted for publication

We study Thouless pumping and arresting of gap solitons in a two-component Bose gas loaded into an optical superlattice. We show that, depending on the atomic interactions and chemical potentials, the two solitons can be simultaneously pumped or trapped, but we also identify regimes where one soliton is pumped and the other arrested. These behaviors can be understood by considering an effective model of the system based on a variational approach, which reveals that the soliton width is a suitable qualifier for the observed behaviours: solitons with a larger width get transported, while solitons with a smaller width get trapped. Since these width can be controlled by tuning interactions, it should be possible to observe all behaviours experimentally., Comment: 7 pages, 3 figures

Sharding is used to improve the scalability and performance of blockchain systems. We investigate the stability of blockchain sharding, where transactions are continuously generated by an adversarial model. The system consists of $n$ processing nodes that are divided into $s$ shards. Following the paradigm of classical adversarial queuing theory, transactions are continuously received at injection rate $\rho \leq 1$ and burstiness $b > 0$. We give an absolute upper bound $\max\{ \frac{2}{k+1}, \frac{2}{ \left\lfloor\sqrt{2s}\right\rfloor}\}$ on the maximum injection rate for which any scheduler could guarantee bounded queues and latency of transactions, where $k$ is the number of shards that each transaction accesses. We next give a basic distributed scheduling algorithm for uniform systems where shards are equally close to each other. To guarantee stability, the injection rate is limited to $\rho \leq \max\{ \frac{1}{18k}, \frac{1}{\lceil 18 \sqrt{s} \rceil} \}$. We then provide a fully distributed scheduling algorithm for non-uniform systems where shards are arbitrarily far from each other. By using a hierarchical clustering of the shards, stability is guaranteed with injection rate $\rho \leq \frac{1}{c_1d \log^2 s} \cdot \max\{ \frac{1}{k}, \frac{1}{\sqrt{s}} \}$, where $d$ is the worst distance of any transaction to the shards it will access, and $c_1$ is some positive constant. We also conduct simulations to evaluate the algorithms and measure the average queue sizes and latency throughout the system. To our knowledge, this is the first adversarial stability analysis of sharded blockchain systems., Comment: 11 pages, 3 figures

Modern detector technology and highly brilliant fourth-generation synchrotrons allow to improve the temporal resolution in time-resolved diffraction studies. Profiting from this, we applied temperature scanning X-ray photon correlation spectroscopy (XPCS) to probe the dynamics of a Pt-based metallic glass former in the glass, glass transition region, and supercooled liquid, covering up to six orders of magnitude in time scales. Our data demonstrates that the structural alpha-relaxation process is still observable in the glass, although it is partially masked by a faster source of decorrelation observed at atomic scale. We present an approach that interprets these findings as the superposition of heterogeneous liquid-like and stress-driven ballistic-like atomic motions. This work not only extends the dynamical range probed by standard isothermal XPCS, but also clarifies the fate of the alpha-relaxation across the glass transition and provides a new perception on the anomalous, compressed temporal decay of the density-density correlation functions observed in metallic glasses and many out-of-equilibrium soft materials.

Connectivity is a main driver for the ongoing megatrend of automated mobility: future Cooperative Intelligent Transport Systems (C-ITS) will connect road vehicles, traffic signals, roadside infrastructure, and even vulnerable road users, sharing data and compute for safer, more efficient, and more comfortable mobility. In terms of communication technology for realizing such vehicle-to-everything (V2X) communication, the WLAN-based peer-to-peer approach (IEEE 802.11p, ITS-G5 in Europe) competes with C-V2X based on cellular technologies (4G and beyond). Irrespective of the underlying communication standard, common message interfaces are crucial for a common understanding between vehicles, especially from different manufacturers. Targeting this issue, the European Telecommunications Standards Institute (ETSI) has been standardizing V2X message formats such as the Cooperative Awareness Message (CAM). In this work, we present V2AIX, a multi-modal real-world dataset of ETSI ITS messages gathered in public road traffic, the first of its kind. Collected in measurement drives and with stationary infrastructure, we have recorded more than 285 000 V2X messages from more than 2380 vehicles and roadside units in public road traffic. Alongside a first analysis of the dataset, we present a way of integrating ETSI ITS V2X messages into the Robot Operating System (ROS). This enables researchers to not only thoroughly analyze real-world V2X data, but to also study and implement standardized V2X messages in ROS-based automated driving applications. The full dataset is publicly available for non-commercial use at v2aix.ika.rwth-aachen.de., Comment: 7 pages; Accepted to be published as part of the 27th International Conference on Intelligent Transportation Systems (ITSC), Edmonton, Canada, September 24-27, 2024

This paper evaluated the impact of synthetic images on Morphing Attack Detection (MAD) using a Siamese network with a semi-hard-loss function. Intra and cross-dataset evaluations were performed to measure synthetic image generalisation capabilities using a cross-dataset for evaluation. Three different pre-trained networks were used as feature extractors from traditional MobileNetV2, MobileNetV3 and EfficientNetB0. Our results show that MAD trained on EfficientNetB0 from FERET, FRGCv2, and FRLL can reach a lower error rate in comparison with SOTA. Conversely, worse performances were reached when the system was trained only with synthetic images. A mixed approach (synthetic + digital) database may help to improve MAD and reduce the error rate. This fact shows that we still need to keep going with our efforts to include synthetic images in the training process., Comment: Arxiv version of CIARP2023 - fixed typo errors

For systems in equilibrium, quantum statistical physics provides a number of general theorems and relations that are not tied to specific microscopic models, one example being the fluctuation-dissipation theorem. Much less is known for nonequilibrium situations. In this work, we discuss certain properties of the power-spectrum tensor for systems in general steady-states, i.e. stationary states not necessarily corresponding to equilibrium configurations. In our analyses, we do not make any direct connection to specific models for the underlying microscopic dynamics and, therefore, our results can be applied to a large variety of systems. We also connect the power-spectrum tensor to other quantities that characterize these systems and, where appropriate, compare with the equilibrium counterparts. As an application, we consider the specific problem of quantum friction, where, at zero temperature, a contactless quantum-electrodynamic drag force acts on a particle that moves in close proximity to an arrangement of material bodies. Specifically, we show how the additional information about the system's physics facilitates the derivation of more precise constraints on the power spectrum and its functional dependencies., Comment: 13 pages, 1 figure

We investigate the structural and electronic origin of antiferromagnetic (AFM) coupling in the Yttrium iron garnet (YIG) and permalloy (Py) bilayer system at the atomic level. Ferromagnetic Resonance (FMR) reveal unique hybrid modes in samples prepared with surface ion milling, indicative of antiferromagnetic exchange coupling at the YIG/Py interface. Using atomic resolution scanning transmission electron microscopy (STEM), we found that AFM coupling appears at the YIG/Py interface of the tetrahedral YIG surface formed with ion milling. The STEM measurements suggest that the interfacial AFM coupling is predominantly driven by an oxygen-mediated super-exchange coupling mechanism, which is confirmed by the density functional theory (DFT) calculations to be energetically favorable. Thus, the combined experimental and theoretical results reveal the critical role of interfacial atomic structure in determining the type magnetic coupling in a YIG/ferromagnet heterostructure, and prove that the interfacial structure can be experimentally tuned by surface ion-milling.

Introduction: With the rapid advances in large language models (LLMs), there have been numerous new open source as well as commercial models. While recent publications have explored GPT-4 in its application to extracting information of interest from radiology reports, there has not been a real-world comparison of GPT-4 to different leading open-source models. Materials and Methods: Two different and independent datasets were used. The first dataset consists of 540 chest x-ray reports that were created at the Massachusetts General Hospital between July 2019 and July 2021. The second dataset consists of 500 chest x-ray reports from the ImaGenome dataset. We then compared the commercial models GPT-3.5 Turbo and GPT-4 from OpenAI to the open-source models Mistral-7B, Mixtral-8x7B, Llama2-13B, Llama2-70B, QWEN1.5-72B and CheXbert and CheXpert-labeler in their ability to accurately label the presence of multiple findings in x-ray text reports using different prompting techniques. Results: On the ImaGenome dataset, the best performing open-source model was Llama2-70B with micro F1-scores of 0.972 and 0.970 for zero- and few-shot prompts, respectively. GPT-4 achieved micro F1-scores of 0.975 and 0.984, respectively. On the institutional dataset, the best performing open-source model was QWEN1.5-72B with micro F1-scores of 0.952 and 0.965 for zero- and few-shot prompting, respectively. GPT-4 achieved micro F1-scores of 0.975 and 0.973, respectively. Conclusion: In this paper, we show that while GPT-4 is superior to open-source models in zero-shot report labeling, the implementation of few-shot prompting can bring open-source models on par with GPT-4. This shows that open-source models could be a performant and privacy preserving alternative to GPT-4 for the task of radiology report classification.

Strongly correlated impurities immersed in a Bose-Einstein condensate (BEC) can form a periodic structure of tightly localized single atoms due to competing inter- and intra-species interactions, leading to a self-organized pinned state. In this work, we show numerically that the impurities in the self-pinned state form a soliton-train, as a consequence of a BEC-mediated attractive self-interaction and ordering due to the exclusion principle. The dynamics of the impurities possess similar characteristics to bright matter-wave solitons as they appear in attractive BECs, however in the few impurities case, the detailed nature of collisions is determined by their quantum statistics., Comment: 7 pages, 4 figures

We illustrate how purpose-specific, graphical modeling enables application experts with different levels of expertise to collaboratively design and then produce complex applications using their individual, purpose-specific modeling language. Our illustration includes seven graphical Integrated Modeling Environments (IMEs) that support full code generation, as well as four browser-based applications that were modeled and then fully automatically generated and produced using DIME, our most complex graphical IME. While the seven IMEs were chosen to illustrate the types of languages we support with our Language-Driven Engineering (LDE) approach, the four DIME products were chosen to give an impression of the power of our LDE-generated IMEs. In fact, Equinocs, Springer Nature's future editorial system for proceedings, is also being fully automatically generated and then deployed at their Dordrecht site using a deployment pipeline generated with Rig, one of the IMEs presented. Our technology is open source and the products presented are currently in use., Comment: 43 pages, 30 figures

The Fourier harmonics, $v_2$ and $v_3$ of negative pions are measured at center-of-mass energy per nucleon pair of $\sqrt{s_{\mathrm{NN}}}$= 17.3 GeV around midrapidity by the CERES/NA45 experiment at the CERN SPS in 0--30\% central PbAu collisions with a mean centrality of 5.5\%. The analysis is performed in two centrality bins as a function of the transverse momentum $\mathrm{p_{\mathrm{T}}}$ from 0.05 GeV/$c$ to more than 2 GeV/$c$. This is the first measurement of the $v^{1/3}_{3}/v^{1/2}_{2}$ ratio as a function of transverse momentum at SPS energies, that reveals, independently of the hydrodynamic models, hydrodynamic behavior of the formed system. For $\mathrm{p_{\mathrm{T}}}$ above 0.5 GeV/$c$, the ratio is nearly flat in accordance with the hydrodynamic prediction and as previously observed by the ATLAS and ALICE experiments at the much higher LHC energies. The results are also compared with the SMASH-vHLLE hybrid model predictions., Comment: 8 pages, 5 figures

A dataset is confounded if it is most easily solved via a spurious correlation, which fails to generalize to new data. In this work, we show that, in a continual learning setting where confounders may vary in time across tasks, the challenge of mitigating the effect of confounders far exceeds the standard forgetting problem normally considered. In particular, we provide a formal description of such continual confounders and identify that, in general, spurious correlations are easily ignored when training for all tasks jointly, but it is harder to avoid confounding when they are considered sequentially. These descriptions serve as a basis for constructing a novel CLEVR-based continually confounded dataset, which we term the ConCon dataset. Our evaluations demonstrate that standard continual learning methods fail to ignore the dataset's confounders. Overall, our work highlights the challenges of confounding factors, particularly in continual learning settings, and demonstrates the need for developing continual learning methods to robustly tackle these.

The recognition performance of biometric systems strongly depends on the quality of the compared biometric samples. Motivated by the goal of establishing a common understanding of face image quality and enabling system interoperability, the committee draft of ISO/IEC 29794-5 introduces expression neutrality as one of many component quality elements affecting recognition performance. In this study, we train classifiers to assess facial expression neutrality using seven datasets. We conduct extensive performance benchmarking to evaluate their classification and face recognition utility prediction abilities. Our experiments reveal significant differences in how each classifier distinguishes "neutral" from "non-neutral" expressions. While Random Forests and AdaBoost classifiers are most suitable for distinguishing neutral from non-neutral facial expressions with high accuracy, they underperform compared to Support Vector Machines in predicting face recognition utility.

Shortcuts to adiabaticity (STA) are powerful tools that can be used to control quantum systems with high fidelity. They work particularly well for single particle and non-interacting systems which can be described exactly and which possess invariant or self-similar dynamics. However, finding an exact STA for strongly correlated many-body systems can be difficult, as their complex dynamics may not be easily described, especially for larger systems that do not possess self-similar solutions. Here, we design STAs for one-dimensional bosonic gas in the Tonks--Girardeau limit by using a mean-field approach that succinctly captures the strong interaction effects through a quintic nonlinear term in the Schr\"odinger equation. We show that for the case of the harmonic oscillator with a time-dependent trap frequency the mean-field approach works exactly and recovers the well-known STA from literature. To highlight the robustness of our approach we also show that it works effectively for anharmonic potentials, achieving higher fidelities than other typical control techniques., Comment: 8 pages, 5 figures