University of Luxembourg

Unmanned aerial vehicles (UAVs) have become essential in advancing multi-access edge computing (MEC), providing flexible platforms that enhance network capacity, coverage, and efficiency while reducing latency and improving communication quality. Integrating reconfigurable intelligent surfaces (RIS) with UAV-based MEC systems further elevates these capabilities, delivering significant gains in computational power, energy efficiency (EE), and physical layer security (PLS). However, managing the complexity of RIS within UAV networks requires sophisticated optimization strategies. This survey offers a comprehensive analysis of the fundamentals of RIS, UAVs, and MEC, followed by an in-depth examination of RIS configurations in UAV-based MEC systems, including static, dynamic, and hybrid models. We evaluate the benefits and challenges of RIS integration, such as improved communication, enhanced computational efficiency, optimized energy use, better task management, and strengthened security. In addition, the survey explores the latest advancements in RIS-assisted UAVs for MEC, focusing on boosting computational capacity, minimizing delay, maximizing EE, and enhancing security. To provide a thorough exploration of these topics, detailed summary tables are included, offering a comparative analysis of methodologies, performance metrics, and scenarios from recent studies. Furthermore, the survey presents key lessons learned from current research and identifies future research directions crucial for fully realizing the potential of RIS-enhanced UAV-based MEC systems in next-generation networks.

We study the deformation complex of a canonical morphism i from the properad of (degree shifted) Lie bialgebras $\textbf{Lieb}_{c,d}$ to its polydifferential version $\mathcal {D}(\textbf{Lieb}_{c,d})$ and show that it is quasi-isomorphic to the oriented graph complex $\textbf{GC}^{{\text {or}}}_{c+d+1}$, up to one rescaling class. As the latter complex is quasi-isomorphic to the original graph complex $\textbf{GC}_{c+d}$, we conclude that for c+d=2 the space of homotopy non-trivial infinitesimal deformations of the canonical map i can be identified with the Grothendieck–Teichmüller Lie algebra $\mathfrak {grt}$; moreover, every such an infinitesimal deformation extends to a genuine deformation of the canonical morphism i from $\textbf{Lieb}_{c,d}$ to $\mathcal {D}(\textbf{Lieb}_{c,d})$. The full deformation complex is described with the help of a new graph complex of so called entangled graphs.

The issue of migrant integration has been a focus of debate by the Council of Europe for many decades. In this context, knowledge of the local language(s) is increasingly recognised as a condition for the acquisition of rights in the host country. It is also a key determinant of academic success and access to higher education. At the University of Luxembourg, several study programmes require simultaneous proficiency in one, two, three or even four languages, and while this policy may have its benefits, it can also represent a challenge, especially for foreign students. In this article, we use selected survey results to examine foreign students’ perceptions of the multilingual higher education environment at the University of Luxembourg. The results show that multilingual educational policies can represent a risk for the inclusion of some foreign students. However, the findings also reveal that the process of inclusion really begins with teachers. Language teachers in particular are perceived by foreign students as resource people from whom they primarily expect linguistic, emotional and motivational support. The survey also shows that foreign students pay particular attention to teaching methods – including those designed around digital technologies, which are often well received – as well as the professional skills and attitudes of teaching staff, and that this in turn enables them to decide whether they can develop a relationship of trust and collaboration with their teacher.

As the demand for remote sensing increases, it is gradually becoming possible for remote sensing satellites to access large-scale communication constellations through laser inter-satellite links, enabling high-throughput data backhaul. This paper addresses the inter-layer topology planning problem using potential game theory for the first time, strategically framing it as a decision-making problem for remote sensing satellites to access communication satellites. Then, theoretical derivation confirms that the above problem is a potential game and verifies the existence of Nash equilibrium. Additionally, considering factors such as laser link establishment time, cross-layer link visibility time consumption rate, mission transmission delay, and communication satellite loading level, a potential game strategy selection probability update algorithm (PG) based on revenue contribution is proposed. Finally, the superior performance of the PG algorithm in terms of task completion, transmission delay, and transport layer network load is effectively demonstrated through two scenarios involving the Starlink&DOVE and GW&R-SAT constellations.

Achieving a high level of immersion and adaptation in virtual reality (VR) requires precise measurement and representation of user state. While extrinsic physical characteristics such as locomotion and pose can be accurately tracked in real-time, reliably capturing mental states is more challenging. Quantitative psychology allows considering more intrinsic features like emotion, attention, or cognitive load. Time perception, in particular, is strongly tied to users' mental states, including stress, focus, and boredom. However, research on objectively measuring the pace at which we perceive the passage of time is scarce. In this work, we investigate the potential of electroencephalography (EEG) as an objective measure of time perception in VR, exploring neural correlates with oscillatory responses and time-frequency analysis. To this end, we implemented a variety of time perception modulators in VR, collected EEG recordings, and labeled them with overestimation, correct estimation, and underestimation time perception states. We found clear EEG spectral signatures for these three states, that are persistent across individuals, modulators, and modulation duration. These signatures can be integrated and applied to monitor and actively influence time perception in VR, allowing the virtual environment to be purposefully adapted to the individual to increase immersion further and improve user experience. A free copy of this paper and all supplemental materials are available at https://vrarlab.uni.lu/pub/brain-signatures .

Modern software has been an integral part of everyday activities in many disciplines and application contexts. Introducing intelligent automation by leveraging artificial intelligence (AI) led to breakthroughs in many fields. The effectiveness of AI can be attributed to several factors, among which is the increasing availability of data. Regulations such as the General Data Protection Regulation (GDPR) in the European Union (EU) are introduced to ensure the protection of personal data. Software systems that collect, process or share personal data are subject to compliance with such regulations. Developing compliant software depends heavily on addressing legal requirements stipulated in applicable regulations, a central activity in the requirements engineering (RE) phase of the software development process. RE is concerned with specifying and maintaining requirements of a system-to-be, including legal requirements. Legal agreements which describe the policies organizations implement for processing personal data can provide an additional source to regulations for eliciting legal requirements. In this chapter, we explore a variety of methods for analysing legal requirements and exemplify them on GDPR. Specifically, we describe possible alternatives for creating machine-analysable representations from regulations, survey the existing automated means for enabling compliance verification against regulations and further reflect on the current challenges of legal requirements analysis. Analysing legal requirements is a core RE activity that relies to a large extent on natural language processing technologies. This chapter contributes with the necessary knowledge required for eliciting, representing and verifying legal requirements.

Oscillations of conductance observed in strong magnetic fields are a striking manifestation of the quantum dynamics of charge carriers in solids. The large charge carrier density in typical metals sets the scale of oscillations in both electrical and thermal conductivity, which characterize the Fermi surface. In semimetals, thermal transport at low-charge carrier density is expected to be phonon dominated, yet several experiments observe giant quantum oscillations in thermal transport. This raises the question of whether there is an overarching mechanism leading to sizable oscillations that survives in phonon-dominated semimetals. In this work, we show that such a mechanism exists. It relies on the peculiar phase-space allowed for phonon scattering by electrons when only a few Landau levels are filled. Our measurements on the Dirac semimetal ZrTe 5 support this counterintuitive mechanism through observation of pronounced thermal quantum oscillations, since they occur in similar magnitude and phase in directions parallel and transverse to the magnetic field. Our phase-space argument applies to all low-density semimetals, topological or not, including graphene and bismuth. Our work illustrates that phonon absorption can be leveraged to reveal degrees of freedom through their imprint on longitudinal thermal transport.

We analyze the propagation characteristics of a General Model vortex Higher-order cosh-Gaussian beam (GMvHchGB) in a turbulent oceanic medium. The beam’s intensity expression is derived using the Huygens–Fresnel integral formula. Through numerical simulations, the average intensity distribution is evaluated, focusing on the effects of oceanic turbulence and the incident beam parameters. The results indicate that the received intensity depends on the initial parameters and the oceanic conditions. Notably, under stronger oceanic turbulence, the GMvHchGB a transformation, losing its initial structure and quickly evolving into a Gaussian profile. This transformation is influenced by a reduction in the dissipation rate of turbulent kinetic energy per unit mass or an increase in the dissipation rate of mean-square temperature and the ratio of temperature to salinity fluctuation. Additionally, the initial beam parameters significantly affect the GMvHchGB’s intensity in the oceanic turbulent medium. These findings offer insights into potential applications in underwater optical communication between ships, divers, and submarines, as well as imaging systems.

Aims Evidence on outcomes of treating type 1 diabetes (T1D) with long‐acting basal insulins in low‐resourced settings is lacking. This study aimed to evaluate the impact of switching children and youth with T1D in the low‐income country of Mali from human insulin via syringe to long‐acting biosimilar insulin glargine delivered by reusable pens combined with short‐acting insulin via syringe. Methods A two‐group parallel design randomised trial was conducted enrolling 260 youth aged <25 years, diagnosed with T1D for ≥12 months without prior use of analogue insulin. Youth were randomised 1:1 to either continue receiving current therapy or switch to analogue insulin. The primary outcome was HbA1c, collected at baseline and 3‐monthly for 12 months. Results Primary outcome data were available for 130 (100%) youth in the intervention group and 128 (98.5%) in the control group. Over the 12‐month study period, mean HbA1c decreased from 103 to 65 mmol/mol (11.6%–8.1%) ( p < 0.001) in the intervention group and from 101 to 93 mmol/mol (11.4% to 10.7%) in the control group ( p < 0.01), an absolute difference of 30 mmol/mol (95% CI: −37, −24) ( p < 0.001). The proportion of participants with HbA1c ≥130 mmol/mol (≥14%) decreased from 38.5% to 0% in the intervention group, versus 40.6% to 21.9% in the control group. Conclusions Switching to a basal‐bolus insulin regimen including biosimilar glargine resulted in marked improvements in HbA1c and diabetic ketoacidosis episodes. With relevant training, resources, and support, use of long‐acting analogue insulin for treating T1D in Mali was feasible and acceptable to participants and healthcare professionals.

The increasing exploitation of the Internet of Things (IoT) in military settings has revolutionized the development of interconnected defense systems, resulting in the concept of the Internet of Military Things (IoMT). Within this technological ecosystem, wearable devices, especially smartwatches, have emerged as inevitable tools to improve the operational effectiveness and safety of soldiers. This study examines how smartwatches could function as edge devices to verify the identity of soldiers and to monitor their health in real time. By employing biometrics such as gesture recognition (for example, how wearer checks the time or gives a thumbs up) and meticulously analyzing these patterns, soldiers can be securely authenticated, to access sensitive information and IoT systems. Moreover, smartwatches can track biological signals, including Electrocardiogram (ECG) and Electromyographic (EMG) data, to comprehensively assess soldiers' emotional well-being and strategically respond when necessary. The fusion of technology with edge computing and behavioral biometrics in military wearables represents a groundbreaking advancement in modern warfare tactics and equipment.

Background Child pain‐related injustice appraisals, associated with adverse pain‐related functioning, are commonly assessed using the Injustice Experience Questionnaire (IEQ). However, the IEQ was initially developed for adults. Recent qualitative phenomenological work highlighted pain‐related injustice themes among children that are seemingly not captured by the IEQ. Furthermore, research in adults and children has shown strong associations between the IEQ and both pain catastrophising and disability. These issues raise concerns regarding the content validity and discriminant content validity of the IEQ for paediatric populations. This study assessed the content validity and discriminant content validity of the IEQ items and a set of novel items generated through previous qualitative work. Methods Content and discriminant content validity of the items was assessed by 96 adult judges rating items as measuring child injustice appraisals, as well as measuring competing constructs: pain catastrophising, disability and negative affect. Wilcoxon signed‐rank tests were applied to assess content and discriminant content validity. Results Four of 12 IEQ items displayed content validity as well as discriminant content validity against pain catastrophising and disability. Eight of 13 newly generated items displayed content validity as well as discriminant content validity against pain catastrophising and disability. Only two of all 25 items displayed discriminant content validity against negative affect. Conclusions This study revealed the IEQ to lack discriminant content validity for use in a paediatric context. An item pool was created to assess child pain‐related injustice appraisals, displaying both content validity and discriminant content validity against the competing constructs of pain catastrophising and disability. Significance Statement The current study both reveals issues in applying the IEQ to assess child pain‐related injustice appraisals and advances research on child pain‐related injustice appraisals by providing an item pool displaying both content validity and discriminant content validity against the competing constructs of child pain catastrophising and child disability.

We evaluate the impact of pretraining Graph Transformer architectures on atom-level quantum-mechanical features for the modeling of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drug-like compounds. We compare this pretraining strategy with two others: one based on molecular quantum properties (specifically the HOMO-LUMO gap) and one using a self-supervised atom masking technique. After fine-tuning on Therapeutic Data Commons ADMET datasets, we evaluate the performance improvement in the different models observing that models pretrained with atomic quantum mechanical properties produce in general better results. We then analyze the latent representations and observe that the supervised strategies preserve the pretraining information after fine-tuning and that different pretrainings produce different trends in latent expressivity across layers. Furthermore, we find that models pretrained on atomic quantum mechanical properties capture more low-frequency Laplacian eigenmodes of the input graph via the attention weights and produce better representations of atomic environments within the molecule. Application of the analysis to a much larger non-public dataset for microsomal clearance illustrates generalizability of the studied indicators. In this case the performances of the models are in accordance with the representation analysis and highlight, especially for the case of masking pretraining and atom-level quantum property pretraining, how model types with similar performance on public benchmarks can have different performances on large scale pharmaceutical data. Scientific contribution We systematically compared three different data type/methodologies for pretraining molecular Graphormer with the purpose of modeling ADMET properties as downstream tasks. The learned representations from differently pretrained models were analyzed in addition to comparison of downstream task performances that have been typically reported in similar works. Such examination methodologies, including a newly introduced analysis of Graphormer’s Attention Rollout Matrix, can guide pretraining strategy selection, as corroborated by a performance evaluation on a larger internal dataset.

Mobile software engineering has been a hot research topic for decades. Our fellow researchers have proposed various approaches (with over 7,000 publications for Android alone) in this field that essentially contributed to the great success of the current mobile ecosystem. Existing research efforts mainly focus on popular mobile platforms, namely Android and iOS. OpenHarmony, a newly open-sourced mobile platform, has rarely been considered, although it is the one requiring the most attention as OpenHarmony is expected to occupy one-third of the market in China (if not in the world). To fill the gap, we present to the mobile software engineering community a research roadmap for encouraging our fellow researchers to contribute promising approaches to OpenHarmony. Specifically, we start by presenting a tertiary study of mobile software engineering, attempting to understand what problems have been targeted by the mobile community and how they have been resolved. We then summarize the existing (limited) achievements of OpenHarmony and subsequently highlight the research gap between Android/iOS and OpenHarmony. This research gap eventually helps in forming the roadmap for conducting software engineering research for OpenHarmony.