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The integration of sensorized vessels, enabling real-time data collection and machine learning-driven data analysis marks a pivotal advancement in the maritime industry. This transformative technology not only can enhance safety, efficiency, and sustainability but also usher in a new era of cost-effective and smart maritime transportation in our increasingly interconnected world. This study presents a deep learning-driven anomaly detection system augmented with interpretable machine learning models for identifying performance anomalies in an industrial sensorized vessel, called TUCANA. We Leverage a human-in-the-loop unsupervised process that involves utilizing standard and Long Short-Term Memory (LSTM) autoencoders augmented with interpretable surrogate models, i.e., random forest and decision tree, to add transparency and interpretability to the results provided by the deep learning models. The interpretable models also enable automated rule generation for translating the inference into human-readable rules. Additionally, the process also includes providing a projection of the results using t-distributed stochastic neighbor embedding (t-SNE), which helps with a better understanding of the structure and relationships within the data and assessment of the identified anomalies. We empirically evaluate the system using real data acquired from the vessel TUCANA and the results involve achieving over 80% precision and 90% recall with the LSTM model used in the process. The interpretable models also provide logical rules aligned with expert thinking, and the t-SNE-based projection enhances interpretability. Our system demonstrates that the proposed approach can be used effectively in real-world scenarios, offering transparency and precision in performance anomaly detection.

In Si/SiGe heterostructures, the low-lying excited valley state seriously limit operability and scalability of electron spin qubits. For characterizing and understanding the local variations in valley splitting, fast probing methods with high spatial and energy resolution are lacking. Leveraging the spatial control granted by conveyor-mode spin-coherent electron shuttling, we introduce a method for two-dimensional mapping of the local valley splitting by detecting magnetic field dependent anticrossings of ground and excited valley states using entangled electron spin-pairs as a probe. The method has sub-{\mu}eV energy accuracy and a nanometer lateral resolution. The histogram of valley splittings spanning a large area of 210 nm by 18 nm matches well with statistics obtained by the established but time-consuming magnetospectroscopy method. For the specific heterostructure, we find a nearly Gaussian distribution of valley splittings and a correlation length similar to the quantum dot size. Our mapping method may become a valuable tool for engineering Si/SiGe heterostructures for scalable quantum computing., Comment: 17 pages, 11 Figures

Recent advancements in long-context large language models have attracted significant attention, yet their practical applications often suffer from suboptimal context utilization. This study investigates structuring training data to enhance semantic interdependence, demonstrating that this approach effectively improves context utilization. To this end, we introduce the Structured Packing for Long Context (SPLiCe) method, which utilizes retrieval to collate mutually relevant documents into long and coherent training examples. We validate SPLiCe empirically across models of varying sizes -- 3B, 7B, and 13B -- achieving improved performance in long-context tasks, such as Qasper and HotpotQA. Remarkably, even brief fine-tuning with SPLiCe is sufficient to realize these benefits. Additionally, SPLiCe effectively mitigates the lost-in-middle phenomenon often observed in large models. Our comprehensive analysis of SPLiCe explores its design choices and reveals intriguing transfer effects; for instance, training on programming code enhances performance on natural language tasks., Comment: new experiments with a 13B model

In this work, we analyze the local certification of unitary quantum channels, which is a natural extension of quantum hypothesis testing. A particular case of a quantum channel operating on two systems corresponding to product states at the input, is considered. The goal is to minimize the probability of the type II error, given a specified maximum probability of the type I error, considering assistance through entanglement with auxiliary systems. Our result indicates connection of the local certification problem with a product numerical range of unitary matrices. We show that the optimal local strategy does not need usage of auxiliary systems and requires only single round of one-way classical communication. Moreover, we compare local and global certification strategies and show that typically local strategies are optimal, yet in some extremal cases, where global strategies make no errors, local ones may fail miserably. Finally, some application for local certification of von Neumann measurements are discussed as well.

We analyze in detail a procedure of entangling of two singlet-triplet ($S$-$T_{0}$) qubits operated in a regime when energy associated with the magnetic field gradient, $\Delta B_{z}$, is an order of magnitude smaller than the exchange energy, $J$, between singlet and triplet states [Shulman M. et al., Science 336, 202 (2012)]. We have studied theoretically a single $S$-$T_{0}$ qubit in free induction decay and spin echo experiments. We have obtained analytical expressions for time dependence of components of its Bloch vector for quasistatical fluctuations of $\Delta B_{z}$ and quasistatical or dynamical $1/f^{\beta}$-type fluctuations of $J$. We have then considered the impact of fluctuations of these parameters on the efficiency of the entangling procedure which uses an Ising-type coupling between two $S$-$T_{0}$ qubits. Particularly, we have obtained an analytical expression for evolution of two qubits affected by $1/f^{\beta}$-type fluctuations of $J$. This expression indicates the maximal level of entanglement that can be generated by performing the entangling procedure. Our results deliver also an evidence that in the above-mentioned experiment, the $S$-$T_{0}$ qubits were affected by uncorrelated $1/f^{\beta}$ charge noises., Comment: 13 pages + appendices

We study ways of evaluating the performance of losing projects in participatory budgeting (PB) elections by seeking actions that would have led to their victory. We focus on lowering the projects' costs, obtaining additional approvals for them, and asking supporters to refrain from approving other projects: The larger a change is needed, the less successful is the given project. We seek efficient algorithms for computing our measures and we analyze and compare them experimentally. We focus on the greedyAV, Phragm\'en, and Equal-Shares PB rules.

In this work, we introduce a novel method for Particle Identification (PID) within the scope of the ALICE experiment at the Large Hadron Collider at CERN. Identifying products of ultrarelativisitc collisions delivered by the LHC is one of the crucial objectives of ALICE. Typically employed PID methods rely on hand-crafted selections, which compare experimental data to theoretical simulations. To improve the performance of the baseline methods, novel approaches use machine learning models that learn the proper assignment in a classification task. However, because of the various detection techniques used by different subdetectors, as well as the limited detector efficiency and acceptance, produced particles do not always yield signals in all of the ALICE components. This results in data with missing values. Machine learning techniques cannot be trained with such examples, so a significant part of the data is skipped during training. In this work, we propose the first method for PID that can be trained with all of the available data examples, including incomplete ones. Our approach improves the PID purity and efficiency of the selected sample for all investigated particle species.

X-ray continuum emission of active galactic nuclei (AGNs) may be reflected by circumnuclear dusty tori, producing prominent fluorescence iron lines at X-ray frequencies. Here we discuss the broad-band emission of three radio-loud AGN belonging to the class of compact symmetric objects (CSOs), with detected narrow Fe\,K$\alpha$ lines. CSOs have newly-born radio jets, forming compact radio lobes with projected linear sizes of the order of a few to hundreds of parsecs. We model the radio--to--$\gamma$-ray spectra of compact lobes in {J1407+2827}, J1511+0518, and {J2022+6137}, which are among the nearest and the youngest CSOs known to date, and are characterized by an intrinsic X-ray absorbing column density of $N_{\rm H} > 10^{23}$\,cm$^{-2}$. In addition to the archival data, we analyze the newly acquired \chandra\ X-ray Observatory and Sub-Millimeter Array (SMA) observations, and also refine the $\gamma$-ray upper limits from the \fermi\ Large Area Telescope (LAT) monitoring. The new \chandra\ data exclude the presence of the extended X-ray emission components on scales larger than $1.5^{\prime \prime}$. The SMA data unveil a correlation of the spectral index of the electron distribution in the lobes and $N_{\rm H}$, which can explain the $\gamma$-ray quietness of heavily obscured CSOs. Based on our modeling, we argue that the inverse-Compton emission of compact radio lobes may account for the intrinsic X-ray continuum in all these sources. Furthermore, we propose that the observed iron lines may be produced by a reflection of the lobes' continuum from the surrounding cold dust., Comment: The Astrophysical Journal, in press

Although it is commonly expected that a metal disk placed on the surface of water will sink, our investigation has revealed a surprising phenomenon: a vertical jet directed onto the disk from above can allow it to remain afloat. This result defies intuition, as one would assume that the force of the jet's impact would cause the disk to sink.We have discovered that this phenomenon occurs as a result of water displacement from the top of the disk caused by the impacting jet, operating through a mechanism similar to a classical hydraulic jump. This displacement generates a difference in hydrostatic pressures, resulting in an upward buoyancy force capable of balancing the force of gravity. In contrast to the classical case, here the jump radius is fixed by the geometric parameters of a disk, a phenomenon we refer to as the parametric hydraulic jump. To further explore this effect, we have presented a theoretical model based on scaling laws, which provides the conditions required for the disk to float. The dimensionless scaling constant's value was determined through an independent experiment. Finally, we conducted experiments on the disk's floating and sinking, which showed a good match with the proposed theory.

This paper announces the early release of SpokesBiz, a freely available corpus of conversational Polish developed within the CLARIN-BIZ project and comprising over 650 hours of recordings. The transcribed recordings have been diarized and manually annotated for punctuation and casing. We outline the general structure and content of the corpus, showcasing selected applications in linguistic research, evaluation and improvement of automatic speech recognition (ASR) systems

We present a characterization of simple finite non-degenerate bijective set-theoretic solutions of the Yang-Baxter equation in terms of the algebraic structure of the associated permutation skew left braces. In particular, we prove that they need to have a unique minimal non-zero ideal and modulo this ideal one obtains a trivial skew left brace of cyclic type., Comment: 17 pages

Text-to-image diffusion models have demonstrated unprecedented capabilities for flexible and realistic image synthesis. Nevertheless, these models rely on a time-consuming sampling procedure, which has motivated attempts to reduce their latency. When improving efficiency, researchers often use the original diffusion model to train an additional network designed specifically for fast image generation. In contrast, our approach seeks to reduce latency directly, without any retraining, fine-tuning, or knowledge distillation. In particular, we find the repeated calculation of attention maps to be costly yet redundant, and instead suggest reusing them during sampling. Our specific reuse strategies are based on ODE theory, which implies that the later a map is reused, the smaller the distortion in the final image. We empirically compare these reuse strategies with few-step sampling procedures of comparable latency, finding that reuse generates images that are closer to those produced by the original high-latency diffusion model.

The Glauber-Sudarshan, Wigner and Husimi quasiprobability distributions are indispensable tools in quantum optics. However, although mathematical relations between them are well established, not much is known about their operational connection. In this paper, we prove that a single composition of finite-strength quantum limited amplifier and attenuator channels, known for their noise-adding properties, turns the Glauber-Sudarshan distribution of any input operator into its Wigner distribution, and its Wigner distribution into its Husimi distribution. As we dissect, the considered process, which can be performed in a quantum optical laboratory with relative ease, may be interpreted as realizing a quantum-to-classical transition., Comment: 8 pages

Over the last decade, applications of neural networks (NNs) have spread to various aspects of our lives. A large number of companies base their businesses on building products that use neural networks for tasks such as face recognition, machine translation, and self-driving cars. Much of the intellectual property underpinning these products is encoded in the exact parameters of the neural networks. Consequently, protecting these is of utmost priority to businesses. At the same time, many of these products need to operate under a strong threat model, in which the adversary has unfettered physical control of the product. In this work, we present BarraCUDA, a novel attack on general purpose Graphic Processing Units (GPUs) that can extract parameters of neural networks running on the popular Nvidia Jetson Nano device. BarraCUDA uses correlation electromagnetic analysis to recover parameters of real-world convolutional neural networks.

With increasing attention in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a $s$-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in situ fabricated Nb/$\mathrm{(Bi_{0.15}Sb_{0.85})_2Te_3}$ nano interface. The resulting high interface transparency is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features., Comment: Main manuscript: 11 pages, 6 figures, Supplementary material: 10 pages, 9 figures

In this paper, we explore how members of the scientific community leave academic science and how attrition (defined as ceasing to publish) differs across genders, academic disciplines, and over time. Our approach is cohort-based and longitudinal: We track individual male and female scientists over time and quantify the phenomenon traditionally referred to as 'leaving science.' Using publication metadata from Scopus - a global bibliometric database of publications and citations - we follow the details of the publishing careers of scientists from 38 OECD countries who started publishing in 2000 (N = 142,776) and 2010 (N = 232,843). Our study is restricted to 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine), and we track the individual scholarly output of the two cohorts until 2022. We use survival analysis to compare attrition of men and women scientists. With more women in science and more women within cohorts, attrition is becoming ever less gendered. In addition to the combined aggregated changes at the level of all STEMM disciplines, widely nuanced changes were found to occur at the discipline level and over time. Attrition in science means different things for men versus women depending on the discipline; moreover, it means different things for scientists from different cohorts entering the scientific workforce. Finally, global bibliometric datasets were tested in the current study, opening new opportunities to explore gender and disciplinary differences in attrition., Comment: 33 pages, 10 figures, 3 Tables (plus 21 pp. of Supplementary Material)

The assessment of risk based on historical data faces many challenges, in particular due to the limited amount of available data, lack of stationarity, and heavy tails. While estimation on a short-term horizon for less extreme percentiles tends to be reasonably accurate, extending it to longer time horizons or extreme percentiles poses significant difficulties. The application of theoretical risk scaling laws to address this issue has been extensively explored in the literature. This paper presents a novel approach to scaling a given risk estimator, ensuring that the estimated capital reserve is robust and conservatively estimates the risk. We develop a simple statistical framework that allows efficient risk scaling and has a direct link to backtesting performance. Our method allows time scaling beyond the conventional square-root-of-time rule, enables risk transfers, such as those involved in economic capital allocation, and could be used for unbiased risk estimation in small sample settings. To demonstrate the effectiveness of our approach, we provide various examples related to the estimation of value-at-risk and expected shortfall together with a short empirical study analysing the impact of our method.

We improve a recent universality theorem for the Riemann zeta-function in short intervals due to Antanas Laurin\v{c}ikas with respect to the length of these intervals. Moreover, we prove that the shifts can even have exponential growth. This research was initiated by two questions proposed by Laurin\v cikas in a problem session of a recent workshop on universality., Comment: 14 pages, 1 figure

In order to study the formation mechanism of residents' low-carbon awareness and provide an important basis for traffic managers to guide urban residents to choose low-carbon travel mode, this paper proposes a low-carbon energy-saving travel data feature analysis and mining based on machine learning algorithm. This paper uses data mining technology to analyze the data of low-carbon travel questionnaire, and regards the 15-dimensional problem under the framework of planned behavior theory as the internal cause variable that characterizes residents' low-carbon travel willingness. The author uses K-means clustering algorithm to classify the intensity of residents' low-carbon travel willingness, and applies the results as the explanatory variables to the random forest model to explore the mechanism of residents' social attribute characteristics, travel characteristics, etc. on their low-carbon travel willingness. The experimental results show that based on the Silhouette index test and t-SNE dimensionality reduction, residents' low-carbon travel willingness can be divided into three categories: strong, neutral, and not strong; Based on the importance index, the four most significant factors are the occupation, residence, family composition and commuting time of residents. Conclusion: This method provides policy recommendations for the development and management of urban traffic low-carbon from multiple perspectives.

We show through numerical simulation that the Quantum Alternating Operator Ansatz (QAOA) for higher-order, random-coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from $16$ up to $127$ qubits for $p=1$ up to $p=5$, which allows for straight-forward transfer learning of QAOA angles on instance sizes where exhaustive grid-search is prohibitive even for $p>1$. We use Matrix Product State (MPS) simulation at different bond dimensions to obtain confidence in these results, and we obtain the optimal solutions to these combinatorial optimization problems using CPLEX. In order to assess the ability of current noisy quantum hardware to exploit such parameter concentration, we execute short-depth QAOA circuits (with a CNOT depth of 6 per $p$, resulting in circuits which contain $1420$ two qubit gates for $127$ qubit $p=5$ QAOA) on $100$ higher-order (cubic term) Ising models on IBM quantum superconducting processors with $16, 27, 127$ qubits using QAOA angles learned from a single $16$-qubit instance. We show that (i) the best quantum processors generally find lower energy solutions up to $p=3$ for 27 qubit systems and up to $p=2$ for 127 qubit systems and are overcome by noise at higher values of $p$, (ii) the best quantum processors find mean energies that are about a factor of two off from the noise-free numerical simulation results. Additional insights from our experiments are that large performance differences exist among different quantum processors even of the same generation and that dynamical decoupling significantly improve performance for some, but decrease performance for other quantum processors. Lastly we show $p=1$ QAOA angle mean energy landscapes computed using up to a $414$ qubit quantum computer, showing that the mean QAOA energy landscapes remain very similar as the problem size changes.

Products certified under security certification frameworks such as Common Criteria undergo significant scrutiny during the costly certification process. Yet, critical vulnerabilities, including private key recovery (ROCA, Minerva, TPM-Fail...), get discovered in certified products with high assurance levels. Furthermore, assessing which certified products are impacted by such vulnerabilities is complicated due to the large amount of unstructured certification-related data and unclear relationships between the certified products. To address these problems, we conducted a large-scale automated analysis of Common Criteria certificates. We trained unsupervised models to learn which vulnerabilities from NIST's National Vulnerability Database impact existing certified products and how certified products reference each other. Our tooling automates the analysis of tens of thousands of certification-related documents, extracting machine-readable features where manual analysis is unattainable. Further, we identify the security requirements that are associated with products being affected by fewer and less severe vulnerabilities. This indicates which aspects of certification correlate with higher security. We demonstrate how our tool can be used for better vulnerability mitigation on four case studies of known, high-profile vulnerabilities. All tools and continuously updated results are available at https://seccerts.org

As the integration of wind power accelerates, wind power plants (WPPs) are expected to play a crucial role in ensuring stability in future power grids. This paper examines the nonlinear stability boundary of a multi-converter system in a wind power plant (WPP) connected to an AC power grid via a long HVAC cable. Traditionally, for nonlinear analysis of WPPs, a simplification is adopted wherein the WPP is treated as an aggregation of individual wind turbines (WTs), with a simplified portrayal of the collector network. However, in the presence of different technologies, such as STATCOM, that are placed away from the WTs, the model aggregation will not hold. This paper presents a unified methodology to model and investigate the high-dimensional stability boundary of a WPP with a STATCOM. The stability region of the system, i.e. the region of attraction (RoA), is determined by the reverse time (backwards) trajectory technique. Furthermore, the estimated stability boundary is verified using time-domain simulation studies in PSCAD.

We consider a general family of nonlocal in space and time diffusion equations with space-time dependent diffusivity and prove convergence of finite difference schemes in the context of viscosity solutions under very mild conditions. The proofs, based on regularity properties and compactness arguments on the numerical solution, allow to inherit a number of interesting results for the limit equation. More precisely, assuming H\"older regularity only on the initial condition, we prove convergence of the scheme, space-time H\"older regularity of the solution depending on the fractional orders of the operators, as well as specific blow up rates of the first time derivative. Finally, using the obtained regularity results, we are able to prove orders of convergence of the scheme in some cases. These results are consistent with previous studies. The schemes' performance is further numerically verified using both constructed exact solutions and realistic examples. Our experiments show that multithreaded implementation yields an efficient method to solve nonlocal equations numerically.

Consider a holomorphic map $F: D \to G$ between two domains in ${\mathbb C}^N$. Let $\mathcal F$ denote a family of geodesics for the Kobayashi distance, such that $F$ acts as an isometry on each element of $\mathcal F$. This paper is dedicated to characterizing the scenarios in which the aforementioned condition implies that $F$ is a biholomorphism. Specifically, we establish this when $D$ is a complete hyperbolic domain, and $\mathcal F$ comprises all geodesic segments originating from a specific point. Another case is when $D$ and $G$ are $C^{2+\alpha}$-smooth bounded pseudoconvex domains, and $\mathcal F$ consists of all geodesic rays converging at a designated boundary point of $D$. Furthermore, we provide examples to demonstrate that these assumptions are essentially optimal.

An ESO internal ALMA development study, BRAIN, is addressing the ill-posed inverse problem of synthesis image analysis employing astrostatistics and astroinformatics. These emerging fields of research offer interdisciplinary approaches at the intersection of observational astronomy, statistics, algorithm development, and data science. In this study, we provide evidence of the benefits of employing these approaches to ALMA imaging for operational and scientific purposes. We show the potential of two techniques, RESOLVE and DeepFocus, applied to ALMA calibrated science data. Significant advantages are provided with the prospect to improve the quality and completeness of the data products stored in the science archive and overall processing time for operations. Both approaches evidence the logical pathway to address the incoming revolution in data rates dictated by the planned electronic upgrades. Moreover, we bring to the community additional products through a new package, ALMASim, to promote advancements in these fields, providing a refined ALMA simulator usable by a large community for training and/or testing new algorithms., Comment: 9 pages, 5 figures, MaxEnt2023 conference

In the article "Universal Densities Exist for Every Finite Reference Measure" (IEEE Trans. Inform. Theory, vol. 69, no. 8, pp. 5277--5288, 2023) we neglected to mention relevant contributions of Boris Ryabko. We cited a source by him that contains a construction of the universal density that we claimed to be our own invention without checking the source after drafting the article. Our article was motivated by a preprint by Feutrill and Roughan, about which we had learned when reviewing the PhD thesis by Andrew Feutrill. Whereas we were not allowed to contact Feutrill and Roughan besides the review form, we developed some ideas of theirs further, ignoring that we stepped into the area previously researched by Ryabko. Our published results exceed those by Ryabko but the article should have been refocused to report Ryabko's contributions. In this note, we detail our citation mistakes., Comment: 5 pages, no figures

Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application requirements and may not be adaptive enough to the frequently-changing grid conditions caused by the transition from conventional to renewable power generation. This paper devises a software-defined virtual synchronous condenser (SDViSC) method to address the challenges. Our contributions are fourfold: 1) design of a virtual synchronous condenser (ViSC) to enable full converter wind turbines to provide built-in SC functionalities; 2) engineering SDViSCs to transfer hardware-based ViSC controllers into software services, where a Tustin transformation-based software-defined control algorithm guarantees accurate tracking of fast dynamics under limited communication bandwidth; 3) a software-defined networking-enhanced SDViSC communication scheme to allow enhanced communication reliability and reduced communication bandwidth occupation; and 4) Prototype of SDViSC on our real-time, cyber-in-the-loop digital twin of large-wind-farm in an RTDS environment. Extensive test results validate the excellent performance of SDViSC to support reliable and resilient operations of wind farms under various physical and cyber conditions.

This letter determines the nonlinear stability boundary of a wind power plant (WPP) connected to an AC power grid via a long HVAC cable. The analysis focuses on the slow Phase-Locked Loop (PLL) dynamics, with an assumption that the fast current control dynamics can be neglected. To begin, we propose an aggregated reduced-order wind turbine model. This aggregation can be applied up to a limited frequency, e.g. 400Hz, which aligns with our assumption regarding low-frequency dynamics. The WPP collector and transmission network model is established using impedance/frequency scan approximated around $\pm$5 Hz of the PLL nominal frequency, accounting for the hard saturation limits. The stability boundary of the reduced-order system is determined by reverse time trajectory, offering valuable insights into the WPP's overall stability. The work presents a routine from modelling to nonlinear stability assessment for offshore wind farm applications.

This study explores the integration of the hyper-power sequence, a method commonly employed for approximating the Moore-Penrose inverse, to enhance the effectiveness of an existing preconditioner. The approach is closely related to polynomial preconditioning based on Neumann series. We commence with a state-of-the-art matrix-free preconditioner designed for the saddle point system derived from isogeometric structure-preserving discretization of the Stokes equations. Our results demonstrate that incorporating multiple iterations of the hyper-power method enhances the effectiveness of the preconditioner, leading to a substantial reduction in both iteration counts and overall solution time for simulating Stokes flow within a 3D lid-driven cavity. Through a comprehensive analysis, we assess the stability, accuracy, and numerical cost associated with the proposed scheme.

Open Radio Access Networks (RAN) offer diverse economic opportunities. A transition to a flexible, modular approach within the disaggregated RAN framework is crucial, involving careful planning of RAN architecture and the deployment of specialized software applications. Collaboration across sectors is essential for efficiency and reliability, with the open-source community driving innovation. This paper explores challenges for third-party application developers in Open RAN. It provides a comparative analysis of solutions, focusing on xApp development and implementation. Challenges arise in two areas: the complexities of xApp development, particularly for advanced use cases like beam management, and issues in low-level software implementation within open platforms. In conclusion, key challenges must promote academia-industry collaboration in Open RAN. This paper shares early lessons from xApp development, guiding the field's evolution., Comment: Accepted for publication in IEEE Journal on Selected Areas in Communications

Video generation is important, especially in medicine, as much data is given in this form. However, video generation of high-resolution data is a very demanding task for generative models, due to the large need for memory. In this paper, we propose Memory Efficient Video GAN (MeVGAN) - a Generative Adversarial Network (GAN) which uses plugin-type architecture. We use a pre-trained 2D-image GAN and only add a simple neural network to construct respective trajectories in the noise space, so that the trajectory forwarded through the GAN model constructs a real-life video. We apply MeVGAN in the task of generating colonoscopy videos. Colonoscopy is an important medical procedure, especially beneficial in screening and managing colorectal cancer. However, because colonoscopy is difficult and time-consuming to learn, colonoscopy simulators are widely used in educating young colonoscopists. We show that MeVGAN can produce good quality synthetic colonoscopy videos, which can be potentially used in virtual simulators.

Reversible computation is an emerging computing paradigm that allows any sequence of operations to be executed in reverse order at any point during computation. Its appeal lies in its potential for lowpower computation and its relevance to a wide array of applications such as chemical reactions, quantum computation, robotics, and distributed systems. Reversing Petri nets are a recently-proposed extension of Petri nets that implements the three main forms of reversibility, namely, backtracking, causal reversing, and out-of-causal-order reversing. Their distinguishing feature is the use of named tokens that can be combined together to form bonds. Named tokens along with a history function, constitute the means of remembering past behaviour, thus, enabling reversal. In recent work, we have proposed a structural translation from a subclass of RPNs to the model of Coloured Petri Nets (CPNs), an extension of traditional Petri nets where tokens carry data values. In this paper, we extend the translation to handle RPNs with token multiplicity under the individual-token interpretation, a model which allows multiple tokens of the same type to exist in a system. To support the three types of reversibility, tokens are associated with their causal history and, while tokens of the same type are equally eligible to fire a transition when going forward, when going backwards they are able to reverse only the transitions they have previously fired. The new translation, in addition to lifting the restriction on token uniqueness, presents a refined approach for transforming RPNs to CPNs through a unifying approach that allows instantiating each of the three types of reversibility. The paper also reports on a tool that implements this translation, paving the way for automated translations and analysis of reversible systems using CPN Tools., Comment: The paper is planned to be published in a reputable journal

A theoretical model of two-pion photoproduction is presented. The model encodes the prominent $\rho(770)$ resonance and the expected leading background contribution coming from the Deck mechanism. To validate the model, angular moments are computed and compared with the CLAS dataset. After fitting a number of free parameters, the model provides a good description of the data., Comment: 5 pages, 2 figures, proceedings of 17th International Workshop on Meson Physics (MESON2023), June 22nd to 27th, 2023. arXiv admin note: text overlap with arXiv:2310.18990

We construct a Convolution Quadrature (CQ) scheme for the quasilinear subdiffusion equation and supply it with the fast and oblivious implementation. In particular we find a condition for the CQ to be admissible and discretize the spatial part of the equation with the Finite Element Method. We prove the unconditional stability and convergence of the scheme and find a bound on the error. As a passing result, we also obtain a discrete Gronwall inequality for the CQ, which is a crucial ingredient of our convergence proof based on the energy method. The paper is concluded with numerical examples verifying convergence and computation time reduction when using fast and oblivious quadrature.

In every proposed unification scheme for Active Galactic Nuclei (AGN), an integral element is the presence of circumnuclear dust arranged in torus-like structures. A crucial model parameter in this context is the covering factor (CF), defined as the ratio between the infrared luminosity of the dusty torus $L_{\rm IR}$, and the accretion disk bolometric luminosity $L_{\rm agn}$. Our study aims to determine whether CF evolution is genuine or if selection effects significantly influence it. Based on cross-matched multiwavelength photometrical data from the five major surveys (SDSS, GALEX, UKIDSS, WISE, SPITZER), a sample of almost 2,000 quasars was derived. The main parameters of quasars, such as black hole masses and the Eddington ratios, were calculated based on the spectroscopic data. The data were divided into two redshift bins: Low-$z$ (redshift ~1) and High-$z$ (redshift ~2) quasars. We identified an issue with the accuracy of the WISE W4 filter. Whenever feasible, it is recommended to utilize SPITZER MIPS 24 $\mu$m data. The calculated median CF values for the highest quality SPITZER data are comparable within errors $\log$ CF$_{\textrm{low}-z} = -0.19\pm 0.11$ and $\log$ CF$_{\textrm{high}-z}= -0.18\pm 0.11$. The Efron & Petrosian test confirmed the presence of luminosity evolution with redshift for both $L_{\rm IR}$ and $L_{\rm agn}$. Both the Low-$z$ and High-$z$ samples exhibit a similar correlation between $L_{\rm agn}$ and $L_{\rm IR}$. No discernible evolution of the CF was observed in the subsample of quasars with high SMBH mass bin or high luminosities. The relationship between $L_{\rm IR}$ and $L_{\rm agn}$ deviates slightly from the expected 1:1 scaling. However, no statistically significant dependence of CF on luminosities could be claimed across the entire dataset., Comment: 21 pages, 22 figures, Astronomy & Astrophysics accepted

In the modelling and analysis of large, real systems, the main problem in their efficient processing is the size of the global model. One of the popular approaches that address this issue is the decomposition of such global model into much smaller submodels and interaction between them. In this paper we discuss the translation of multi-agent systems with the common-action-based synchronization to 1-safe Petri nets. We prove that the composition in terms of transition systems is equivalent to the transition-based fusion of nets modelling different agents. We also address the issue of permanent disabling of some parts of the system by constraints implied by the synchronization and discuss the methods of solving it without the computation of the entire global model., Comment: https://ceur-ws.org/Vol-3170/paper8.pdf

A calculation of the angular moments of two-pion photoproduction is presented. The underlying theoretical model encodes the prominent $\rho(770)$ resonance and the expected leading background contribution coming from the Deck mechanism. The model contains a number of free parameters which are fit to experimental data. A good description of the angular moments is obtained., Comment: 5 pages, 3 figures. Prepared as proceedings contribution for the 20th International Conference on Hadron Spectroscopy and Structure (HADRON 2023), Genova, Italy, 5-9/6/2023

Formal verification of strategic abilities is a hard problem. We propose to use the methodology of assume-guarantee reasoning in order to facilitate model checking of alternating-time temporal logic with imperfect information and imperfect recall.

Model checking of strategic abilities is a notoriously hard problem, even more so in the realistic case of agents with imperfect information. Assume-guarantee reasoning can be of great help here, providing a way to decompose the complex problem into a small set of exponentially easier subproblems. In this paper, we propose two schemes for assume-guarantee verification of alternating-time temporal logic with imperfect information. We prove the soundness of both schemes, and discuss their completeness. We illustrate the method by examples based on known benchmarks, and show experimental results that demonstrate the practical benefits of the approach.

Investigating Protostellar Accretion (IPA) is a JWST Cycle~1 GO program that uses NIRSpec IFU and MIRI MRS to obtain 2.9--28~$\mu$m spectral cubes of young, deeply embedded protostars with luminosities of 0.2 to 10,000~L$_{\odot}$ and central masses of 0.15 to 12~M$_{\odot}$. In this Letter, we report the discovery of a highly collimated atomic jet from the Class~0 protostar IRAS~16253$-$2429, the lowest luminosity source ($L_\mathrm{bol}$ = 0.2 $L_\odot$) in the IPA program. The collimated jet is detected in multiple [Fe~II] lines, [Ne~II], [Ni~II], and H~I lines, but not in molecular emission. The atomic jet has a velocity of about 169~$\pm$~15~km\,s$^{-1}$, after correcting for inclination. The width of the jet increases with distance from the central protostar from 23 to~60 au, corresponding to an opening angle of 2.6~$\pm$~0.5\arcdeg. By comparing the measured flux ratios of various fine structure lines to those predicted by simple shock models, we derive a shock {speed} of 54~km\,s$^{-1}$ and a preshock density of 2.0$\times10^{3}$~cm$^{-3}$ at the base of the jet. {From these quantities and using a suite of jet models and extinction laws we compute a mass loss rate between $0.4 -1.1\times10^{-10}~M_{\odot}$~yr~$^{-1}$.} The low mass loss rate is consistent with simultaneous measurements of low mass accretion rate ($2.4~\pm~0.8~\times~10^{-9}~M_{\odot}$~yr$^{-1}$) for IRAS~16253$-$2429 from JWST observations (Watson et al. in prep), indicating that the protostar is in a quiescent accretion phase. Our results demonstrate that very low-mass protostars can drive highly collimated, atomic jets, even during the quiescent phase., Comment: Accepted to ApJL. Comments and feedback welcome

We investigate the dimension-parametric complexity of the reachability problem in vector addition systems with states (VASS) and its extension with pushdown stack (pushdown VASS). Up to now, the problem is known to be $\mathcal{F}_k$-hard for VASS of dimension $3k+2$ (the complexity class $\mathcal{F}_k$ corresponds to the $k$th level of the fast-growing hierarchy), and no essentially better bound is known for pushdown VASS. We provide a new construction that improves the lower bound for VASS: $\mathcal{F}_k$-hardness in dimension $2k+3$. Furthermore, building on our new insights we show a new lower bound for pushdown VASS: $\mathcal{F}_k$-hardness in dimension $\frac k 2 + 4$. This dimension-parametric lower bound is strictly stronger than the upper bound for VASS, which suggests that the (still unknown) complexity of the reachability problem in pushdown VASS is higher than in plain VASS (where it is Ackermann-complete).

We study a $d$-dimensional non-symmetric strictly $\alpha$-stable L\'{e}vy process $\mathbf{X}$, whose spherical density is bounded and bounded away from the origin. First, we give sharp two-sided estimates on the transition density of $\mathbf{X}$ killed when leaving an arbitrary $\kappa$-fat set. We apply these results to get the existence of the Yaglom limit for arbitrary $\kappa$-fat cone. In the meantime we also obtain the spacial asymptotics of the survival probability at the vertex of the cone expressed by means of the Martin kernel for $\Gamma$ and its homogeneity exponent. Our results hold for the dual process $\widehat{\mathbf{X}}$, too., Comment: 26 pages, 1 figure

The aim of this paper is to give natural examples of $\mathbf{\Sigma}_1^1$-complete and $\mathbf{\Pi}_1^1$-complete sets. In the first part, we consider ideals on $\omega$. In particular, we show that the Hindman ideal $\mathcal{H}$ is $\mathbf{\Pi}_1^1$-complete and consider a number of ideals generated in the similar fashion. Moreover, we show that the ideal $\mathcal{D}$ is also $\mathbf{\Pi}_1^1$-complete. In the second part, we focus on families of trees (on $\omega$ and $2$) containing a specific tree type. We show the connection between two topics and explore some classical tree types (like Sacks and Miller)., Comment: 12 pages