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The aim of this paper is to extend Washburn's capillary rise equation by incorporating a slip condition at the pipe wall. The governing equation is derived using fundamental principles from continuum mechanics. A new scaling is introduced, allowing for a systematic analysis of different flow regimes. We prove the global-in-time existence and uniqueness of a bounded positive solution to Washburn's equation that includes the slip parameter, as well as the continuous dependence of the solution in the maximum norm on the initial data. Thus, the initial-value problem for Washburn's equation is shown to be well-posed in the sense of Hadamard. Additionally, we show that the unique equilibrium solution may be reached either monotonically or in an oscillatory fashion, similarly to the no-slip case. Finally, we determine the basin of attraction for the system, ensuring that the equilibrium state will be reached from the initial data we impose. These results hold for any positive value of the nondimensional slip parameter in the model, and for all values of the ratio $h_0/h_e$ in the range $[0,3/2]$, where $h_0$ is the initial height of the fluid column and $h_e$ is its equilibrium height.

We present an approach to Audio-Visual Speech Recognition that builds on a pre-trained Whisper model. To infuse visual information into this audio-only model, we extend it with an AV fusion module and LoRa adapters, one of the most up-to-date adapter approaches. One advantage of adapter-based approaches, is that only a relatively small number of parameters are trained, while the basic model remains unchanged. Common AVSR approaches train single models to handle several noise categories and noise levels simultaneously. Taking advantage of the lightweight nature of adapter approaches, we train noise-scenario-specific adapter-sets, each covering individual noise-categories or a specific noise-level range. The most suitable adapter-set is selected by previously classifying the noise-scenario. This enables our models to achieve an optimum coverage across different noise-categories and noise-levels, while training only a minimum number of parameters. Compared to a full fine-tuning approach with SOTA performance our models achieve almost comparable results over the majority of the tested noise-categories and noise-levels, with up to 88.5% less trainable parameters. Our approach can be extended by further noise-specific adapter-sets to cover additional noise scenarios. It is also possible to utilize the underlying powerful ASR model when no visual information is available, as it remains unchanged., Comment: Accepted at ICASSP 2025

The International Semantic Web Research School (ISWS) is a week-long intensive program designed to immerse participants in the field. This document reports a collaborative effort performed by ten teams of students, each guided by a senior researcher as their mentor, attending ISWS 2023. Each team provided a different perspective to the topic of creative AI, substantiated by a set of research questions as the main subject of their investigation. The 2023 edition of ISWS focuses on the intersection of Semantic Web technologies and Creative AI. ISWS 2023 explored various intersections between Semantic Web technologies and creative AI. A key area of focus was the potential of LLMs as support tools for knowledge engineering. Participants also delved into the multifaceted applications of LLMs, including legal aspects of creative content production, humans in the loop, decentralised approaches to multimodal generative AI models, nanopublications and AI for personal scientific knowledge graphs, commonsense knowledge in automatic story and narrative completion, generative AI for art critique, prompt engineering, automatic music composition, commonsense prototyping and conceptual blending, and elicitation of tacit knowledge. As Large Language Models and semantic technologies continue to evolve, new exciting prospects are emerging: a future where the boundaries between creative expression and factual knowledge become increasingly permeable and porous, leading to a world of knowledge that is both informative and inspiring., Comment: Technical Report

Here we present results from our spectroscopic follow-up of SDSS J2320+0024, a candidate binary supermassive black hole (SMBH) with a suspected sub-pc separation, identified by a 278-day periodicity observed in its multi-band optical light curves. We investigate the dramatic variability of the complex Mg II emission line profile aiming to test the alignments of the observed photometric light curves and the spectroscopic signatures in the context of the binary SMBH system. We extract the pure broad Mg II line from the newly obtained Gemini and Magellan spectra and measure the emission line parameters to reveal fundamental dynamical parameters of the SMBHs binary system. We adopt the PoSKI sub-pc binary SMBH model, which includes broad-line region (BLR) around less massive component and a circumbinary BLR, to interpret the observed variability in the spectral profile. We find that the Mg II line profile has a distinctive complex shape with the asymmetry and two peaks present which is varying across recent and archival observations. The temporal variability of the Mg II line profile may be associated with the emission from the binary SMBH system consisting of components with masses $M_1 = 2 \times 10^7 \, M_{\odot}$ and $M_2 = 2 \times 10^8 \, M_{\odot}$, and eccentricity e = 0.1. With an total estimated mass of $\sim 10^9 M_{\odot}$ and a subannual orbital period, this system may be a rare example of high-mass compact candidate of SMBH binary, thus important for further investigations of the evolution of the binary system. This study is a prototype of synergies of spectroscopic follow-up and future massive time-domain photometric surveys like Vera C. Rubin Observatory Legacy Survey of Space and Time., Comment: Accepted for publication in A&A

We analyze solutions of Chamseddine's topological gravity in four space-time dimensions and discover various black hole solutions with(out) torsion as well as those that describe naked singularities. Because all of the solutions belong to the sector with vanishing scalar fields, they share peculiar trait that all conserved charges are vanishing., Comment: LaTeX, 12 pages, no figures

Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable outcomes or have been used in questionable manners. As a result, there has been a surge in public and academic discussions about aspects that AI systems must fulfill to be considered trustworthy. In this paper, we synthesize existing conceptualizations of trustworthy AI along six requirements: 1) human agency and oversight, 2) fairness and non-discrimination, 3) transparency and explainability, 4) robustness and accuracy, 5) privacy and security, and 6) accountability. For each one, we provide a definition, describe how it can be established and evaluated, and discuss requirement-specific research challenges. Finally, we conclude this analysis by identifying overarching research challenges across the requirements with respect to 1) interdisciplinary research, 2) conceptual clarity, 3) context-dependency, 4) dynamics in evolving systems, and 5) investigations in real-world contexts. Thus, this paper synthesizes and consolidates a wide-ranging and active discussion currently taking place in various academic sub-communities and public forums. It aims to serve as a reference for a broad audience and as a basis for future research directions., Comment: Accepted in Frontiers in Big Data and AI, Research Topic: Towards Fair AI for Trustworthy Artificial Intelligence

The abilities of traditional perimeter-based security architectures are rapidly decreasing as more enterprise assets are moved toward the cloud environment. From a security viewpoint, the Zero Trust framework can better track and block external attackers while limiting security breaches resulting from insider attacks in the cloud paradigm. Furthermore, Zero Trust can better accomplish access privileges for users and devices across cloud environments to enable the secure sharing of resources. Moreover, the concept of zero trust architecture in cloud computing requires the integration of complex practices on multiple layers of system architecture, as well as a combination of a variety of existing technologies. This paper focuses on authentication mechanisms, calculation of trust score, and generation of policies in order to establish required access control to resources. The main objective is to incorporate an unbiased trust score as a part of policy expressions while preserving the configurability and adaptiveness of parameters of interest. Finally, the proof-of-concept is demonstrated on a micro-cloud plat-form solution., Comment: 10 pages, 2 figures

The immense shift to cloud computing has brought changes in security and privacy requirements, impacting critical Identity Management services. Currently, many IdM systems and solutions are accessible as cloud services, delivering identity services for applications in closed domains and the public cloud. This research paper centres on identity management in distributed environments, emphasising the importance of robust up to date authorisation mechanisms. The paper concentrates on implementing robust security paradigms to minimise communication overhead among services while preserving privacy and access control. The key contribution focuses on solving the problem of restricted access to resources in cases when the authentication token is still valid, but permissions are updated. The proposed solution incorporates an Identity and Access Management server as a component that authenticates all external requests. The IAM server key responsibilities include maintaining user data, assigning privileges within the system, and authorisation. Furthermore, it empowers users by offering an Application Programming Interface for managing users and their rights within the same organisation, providing finer granularity in authorisation. The IAM server has been integrated with a configuration dissemination tool designed as a distributed cloud infrastructure to evaluate the solution., Comment: 10 pages, 2 figures

Proliferation of systems that generate enormous amounts of data and operate in real time has led researchers to rethink the current organization of the cloud. Many proposed solutions consist of a number of small data centers in the vicinity of data sources. That creates a highly complex environment, where strict access control is essential. Recommended access control models frequently belong to the Attribute-Based Access Control (ABAC) family. Flexibility and dynamic nature of these models come at the cost of high policy management complexity. In this paper, we explore whether the administrative overhead can be lowered with resource hierarchies. We propose an ABAC model that incorporates user and object hierarchies. We develop a policy engine that supports the model and present a distributed cloud use case. Findings in this paper suggest that resource hierarchies simplify the administration of ABAC models, which is a necessary step towards their further inclusion in real-world systems.

Owing to their cost-effectiveness and flexibility, cloud services have been the default choice for the deployment of innumerable software systems over the years. However, novel paradigms are beginning to emerge, as the cloud can't meet the requirements of increasingly many latency- and privacy-sensitive applications. The distributed cloud model, being one of the attempts to overcome these challenges, places a distributed cloud layer between device and cloud layers, intending to bring resources closer to data sources. As application code should be kept separate from its configuration, especially in highly dynamic cloud environments, there is a need to incorporate configuration primitives in future distributed cloud platforms. In this paper, we present the design and implementation of a configuration management subsystem for an open-source distributed cloud platform. Our solution spreads across the cloud and distributed cloud layers and supports configuration versioning, selective dissemination to nodes in the distributed cloud layer, and logical isolation via namespaces. Our work serves as a demonstration of the feasibility and usability of the new cloud-extending models and provides valuable insight into one of the possible implementations.

Major software failures are reported to be due to misconfiguration. As manual configuration is too error-prone to be deemed a reliable strategy for dynamic and complex systems, automated configuration management has become a standard. Countermeasures against misconfiguration can be focused on prevention or, if failure already occurred, detection. Configuration is often used as a broad term for any set of parameters or system states that dictate how an application will behave, but in this paper, we only focus on parameters consumed on process startup, usually from configuration files. Our objective is to enhance configuration management processes in environments based on the distributed cloud model, a novel cloud model that allows dynamic allocation of strategically located resources. The two mechanisms we propose are configuration validation using schemas and configuration version control with support for detecting differences between configuration versions. Our solution reduces the risk of incorrect configuration as schemas prevent any non-compliant configuration from reaching applications. However, if failure still occurs because the schema was incomplete or a valid configuration revealed existing software bugs, the version control system can precisely locate configuration changes that triggered the failure.

With the rising number of distributed computer systems, from microservice web applications to IoT platforms, the question of reliable communication between different parts of the aforementioned systems is becoming increasingly important. As part of this paper, a task queue, which facilitates reliable asynchronous communication between different services, will be implemented. In order to control the flow of tasks through the queue and limit the load on downstream components, we are going to explore ways of efficiently restricting throughput, and defining priority queues within the task queue service. The research will also take a look at how different aspects of the task queue, such as the underlying persistence layer, affect their performance, reliability, and resource usage. This task queue will be implemented as a component in the already existing platform for managing clusters, constellations

Long-range Rydberg molecules are typically bound in wells formed in their oscillatory potential energy curves. In alkaline Rydberg molecules, bound vibrational states exist even when these potential wells are disrupted by level repulsion from the steep butterfly potential energy curve induced by a scattering shape resonance. The binding in this case is attributed to quantum reflection. However, the rapidly varying regions of the potential energy landscape where quantum reflection occurs often coincide with regions where non-adiabatic coupling becomes significant. By comparing the molecular states calculated within the Born-Oppenheimer approximation, where quantum reflection is the only binding mechanism, with those obtained from the full set of coupled channel equations, we can assess the effects of non-adiabatic coupling on vibrational energies and lifetimes. Our findings show that these couplings can stabilize the molecule by providing an additional barrier which protects the vibrational states from predissociation and non-radiative transitions. There can also be extreme cases where non-adiabatic coupling completely dominates the binding and the molecular lifetimes saturate at the atomic Rydberg lifetime.

Knee osteoarthritis (KOA), a common form of arthritis that causes physical disability, has become increasingly prevalent in society. Employing computer-aided techniques to automatically assess the severity and progression of KOA can greatly benefit KOA treatment and disease management. Particularly, the advancement of X-ray technology in KOA demonstrates its potential for this purpose. Yet, existing X-ray prognosis research generally yields a singular progression severity grade, overlooking the potential visual changes for understanding and explaining the progression outcome. Therefore, in this study, a novel generative model is proposed, namely Identity-Consistent Radiographic Diffusion Network (IC-RDN), for multifaceted KOA prognosis encompassing a predicted future knee X-ray scan conditioned on the baseline scan. Specifically, an identity prior module for the diffusion and a downstream generation-guided progression prediction module are introduced. Compared to conventional image-to-image generative models, identity priors regularize and guide the diffusion to focus more on the clinical nuances of the prognosis based on a contrastive learning strategy. The progression prediction module utilizes both forecasted and baseline knee scans, and a more comprehensive formulation of KOA severity progression grading is expected. Extensive experiments on a widely used public dataset, OAI, demonstrate the effectiveness of the proposed method., Comment: Accepted by ECCV 2024

In this paper, we study and compare the optical and X-ray counterparts of subparsec supermassive black hole binaries (SMBHBs). With that aim, we simulated the profiles of optical spectral lines emitted from the broad line region (BLR) as well as X-ray spectral lines emitted from the relativistic accretion disks around both black holes and compared them with each other. The obtained results showed that SMBHBs could cause a specific, but different variability of the lines from the optical part and Fe K$\alpha$ line, leaving potentially detectable imprints in their profiles. Since these imprints depend on the orbital phase of the system, they could be used for reconstructing the Keplerian orbits of the components in the observed SMBHBs. Moreover, such signatures in the optical and X-ray line profiles of the observed SMBHBs could be used as a tool for the detection of these objects as well as for studying their properties., Comment: 18 pages, 1 table, 10 figures. Accepted for publication in Advances in Space Research

The aim of the study is to compare the standard Maxwell-Stefan model of diffusion with the higher-order one recently derived. This higher-order model takes into account the influence of the complete pressure tensor. A numerical scheme is developed for comparing the two models through numerical simulations of three-component diffusion. It is shown that the higher-order model preserves qualitative features of the diffusion process, but quantitative differences were observed in the behavior of the mixture components.

Agile beam management is key for providing seamless millimeter wave (mm-wave) connectivity given the site-specific spatio-temporal variations of the mm-wave channel. Leveraging non radio frequency (RF) sensor inputs for environment awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-based beam steering. To overcome the lack of diverse publicly available multi-modal mm-wave datasets for the design and evaluation of such novel beam steering approaches, we demonstrate our software-defined radio multi-band mm-wave measurement platform which integrates multi-modal sensors towards environment-aware beam management., Comment: 2 pages, 1 figure

The goal of this expository paper is to present the basics of geometric control theory suitable for advanced undergraduate or beginning graduate students with a solid background in advanced calculus and ordinary differential equations.

We generalize the classical Frobenius integrability theorem to plane fields of class $C^Q$, a regularity class introduced by Reimann [Rei76] for vector fields in Euclidean spaces. A $C^Q$ vector field is uniquely integrable and its flow is a quasiconformal deformation. We show that an a.e. involutive $C^Q$ plane field (defined in a suitable way) in $\mathbb{R}^n$ is integrable, with integral manifolds of class $C^1$.

A simple 'RF-flashlight' (or ground to satellite) interference testbed is proposed to experimentally verify real-time geofencing (RTG) for protecting passive Earth Exploration Satellite Services (EESS) radiometer measurements from 5G or 6G mm-wave transmissions, and ground to satellite propagation models used in the interference modeling of this spectrum coexistence scenario. RTG is a stronger EESS protection mechanism than the current methodology recommended by the ITU based on a worst-case interference threshold while simultaneously enabling dynamic spectrum sharing and coexistence with 5G or 6G wireless networks. Similarly, verifying more sophisticated RF propagation models that include ground topology, buildings, and non-line-of-sight paths will provide better estimates of interference than the current ITU line-of-sight model and, thus, a more reliable basis for establishing a consensus among the spectrum stakeholders.

Hybrid beamforming (HBF) multi-user multiple-input multiple-output (MU-MIMO) is a key technology for unlocking the directional millimeter-wave (mm-wave) nature for spatial multiplexing beyond current codebook-based 5G-NR networks. In order to suppress co-scheduled users' interference, HBF MU-MIMO is predicated on having sufficient radio frequency chains and accurate channel state information (CSI), which can otherwise lead to performance losses due to imperfect interference cancellation. In this work, we propose IABA, a 5G-NR standard-compliant beam pair link (BPL) allocation scheme for mitigating spatial interference in practical HBF MU-MIMO networks. IABA solves the network sum throughput optimization via either a distributed or a centralized BPL allocation using dedicated CSI reference signals for candidate BPL monitoring. We present a comprehensive study of practical multi-cell mm-wave networks and demonstrate that HBF MU-MIMO without interference-aware BPL allocation experiences strong residual interference which limits the achievable network performance. Our results show that IABA offers significant performance gains over the default interference-agnostic 5G-NR BPL allocation, and even allows HBF MU-MIMO to outperform the fully digital MU-MIMO baseline, by facilitating allocation of secondary BPLs other than the strongest BPL found during initial access. We further demonstrate the scalability of IABA with increased gNB antennas and densification for beyond-5G mm-wave networks., Comment: 13 pages, 11 figures. This work has been submitted to IEEE for possible publication (copyright may be transferred without notice, after which this version may no longer be accessible)

Automatic speech recognition (ASR) has reached a level of accuracy in recent years, that even outperforms humans in transcribing speech to text. Nevertheless, all current ASR approaches show a certain weakness against ambient noise. To reduce this weakness, audio-visual speech recognition (AVSR) approaches additionally consider visual information from lip movements for transcription. This additional modality increases the computational cost for training models from scratch. We propose an approach, that builds on a pre-trained ASR model and extends it with an adaptive upstream module, that fuses audio and visual information. Since we do not need to train the transformer structure from scratch, our approach requires a fraction of the computational resources compared to traditional AVSR models. Compared to current SOTA systems like AV-HuBERT, our approach achieves an average improvement of 8.3% in word error rate across different model sizes, noise categories and broad SNR range. The approach allows up to 21% smaller models and requires only a fraction of the computational resources for training and inference compared to common AVSR approaches., Comment: Accepted at ICASSP 2024

In this article we address the question of asymptotic symmetry of massless scalar field at null infinity. We slightly generalize notion of asymptotic symmetry in order to make sense for the theory without gauge symmetry. Derivations of the results are done in two different ways, using Hamiltonian analysis and using covariant phase space. The results are in agreement with the ones previously obtained by various authors for dual 2-form field and with the results obtained starting from scalar soft theorem., Comment: LaTeX, 10 pages, no figures, moderate text changes, minus sign error corrected in one equation, published in Phys. Rev. D

We prove that for every ordered matching $H$ on $t$ vertices, if an ordered $n$-vertex graph $G$ is $\varepsilon$-far from being $H$-free, then $G$ contains $\text{poly}(\varepsilon) n^t$ copies of $H$. This proves a special case of a conjecture of Tomon and the first author. We also generalize this statement to uniform hypergraphs.