University of Luxembourg

We present an algorithm for the repair of parameterized systems that can be represented as well-structured transition systems. The repair problem is, for a given process implementation, to find a refinement such that a given safety property is satisfied by the resulting parameterized system, and deadlocks are avoided. Our algorithm uses a parameterized model checker to determine the correctness of candidate solutions and employs a constraint system to rule out candidates. Parameterized systems that fall into our class include disjunctive systems, pairwise rendezvous systems, broadcast protocols, and certain global synchronization protocols. Moreover, we show that parameterized deadlock detection and similar global properties can be decided in EXPTIME for disjunctive systems, and that deadlock detection is in general undecidable for broadcast protocols.

Transversal skills describe a broad spectrum of skills that are considered to be essential for thriving in today’s society and tackling the challenges of the twenty-first century. Therefore, a high demand is placed on educators to teach these skills to their students. Unfortunately, the conceptualization of transversal skills remains vague with different frameworks reporting on various transversal skills, which complicates a translation of these skills into educational practice and research, thereby making them a “blind spot” in psychological research and educational practice. This paper brings the blind spot on transversal skills to a direct focus. First, we propose a conceptualization of transversal skills through a review and integration of existing frameworks. We organize transversal skills into four core concepts: cognitive skills (e.g., creativity and problem-solving), citizenship (e.g., democratic participation and respect), well-being (e.g., mental and physical health), and social-emotional skills (e.g., collaboration and communication). Second, we highlight possible ways to implement these core concepts into educational practice by providing specific examples on how to integrate specific skills into five subjects: language, mathematics, science, social studies, and arts and music. Third, a research agenda is proposed that considers the structure and underlying processes of transversal skills, their development and interventions at different stages, their predictive validity for success, and cultural differences and diversity.

Understanding the progression of α‐synuclein pathology in neurodegenerative diseases such as Parkinson's disease (PD) is a longstanding challenge. Here, a novel midbrain–hindbrain‐assembloid model that recapitulates the spread of α‐synuclein pathology observed in PD patients, akin to Braak's hypothesis, is presented. Initially, the presence α‐synuclein pathology is demonstrated in the hindbrain organoids. Subsequently, sophisticated tissue engineering methods are employed to create midbrain–hindbrain assembloids. These assembloids allow investigation and description of the spreading of α‐synuclein pathology, as it progresses from the hindbrain components to the midbrain regions within the integrated structure. It is observed that an increase in α‐synuclein in the hindbrain can induce transfer of the pathology into the healthy midbrain, as well as cause changes at the synapse level. The presented model constitutes a robust in vitro platform for investigating the mechanisms underlying α‐synuclein spreading and disease progression, and holding potential for the screening of prospective therapeutics targeting the pathological propagation in PD and related synucleinopathies.

MIRO1 is a mitochondrial outer membrane protein important for mitochondrial distribution, dynamics and bioenergetics. Over the last decade, evidence has pointed to a link between MIRO1 and Parkinson’s disease (PD) pathogenesis. Moreover, a heterozygous MIRO1 mutation (p.R272Q) was identified in a PD patient, from which an iPSC-derived midbrain organoid model was derived, showing MIRO1 mutant-dependent selective loss of dopaminergic neurons. Herein, we use patient-specific iPSC-derived midbrain organoids carrying the MIRO1 p.R272Q mutation to further explore the cellular and molecular mechanisms involved in dopaminergic neuron degeneration. Using single-cell RNA sequencing (scRNAseq) analysis and metabolic modeling we show that the MIRO1 p.R272Q mutation affects the dopaminergic neuron developmental path leading to metabolic deficits and disrupted neuron-astrocyte metabolic crosstalk, which might represent an important pathogenic mechanism leading to their loss.

A growing body of evidence indicates that mental calculation in adults is accompanied by horizontal attention shifts along a mental continuum representing the range of plausible answers. The fast deployment of spatial attention suggests a predictive role in guiding the search for the answer. The link between arithmetic and spatial functions is theoretically justified by the need to alleviate the cognitive load of mental calculation, but the question of how this link establishes during development gives rise to opposing views emphasizing either biological or cultural factors. The role of education, in particular, remains debated in the absence of data covering the period when children learn arithmetic. In this study, we measured gaze movements, as a proxy for attentional shifts, while first-grade elementary school children solved single-digit additions and subtractions. The investigation was scheduled only a few weeks after the formal teaching of symbolic subtraction to assess the role of spatial attention in early learning. Gaze patterns revealed horizontal– but not vertical– attentional shifts, with addition shifting the gaze more rightward than subtraction. The shift was observed as soon as the first operand and the operator were presented, corroborating the view that attention is used to predictively identify the portion of the numerical continuum where the answer is likely to be located, as adult studies suggested. The finding of a similar gaze pattern in adults and six-year-old children who have just learned how to subtract single digits challenges the idea that arithmetic problem solving requires intensive practice to be linked to spatial attention.

An implicit call is a mechanism that triggers the execution of a method m without a direct call to m in the code being analyzed. For instance, in Android apps the Thread.start() method implicitly executes the Thread.run() method. These implicit calls can be conditionally triggered by programmer-specified constraints that are evaluated at run time. For instance, the JobScheduler.schedule() method can be called to implicitly execute the JobService.onStartJob() method only if the device's battery is charging. Such conditional implicit calls can effectively disguise logic bombs , posing significant challenges for both static and dynamic software analyses. Conservative static analysis may produce false-positive alerts due to over-approximation, while less conservative approaches might overlook potential covert behaviors, a serious concern in security analysis. Dynamic analysis may fail to generate the specific inputs required to activate these implicit call targets. To address these challenges, we introduce Archer, a tool designed to resolve conditional implicit calls and extract the constraints triggering execution control transfer. Our evaluation reveals that ① implicit calls are prevalent in Android apps; ② Archer enhances app models’ soundness beyond existing static analysis methods; and ③ Archer successfully infers constraint values, enabling dynamic analyzers to detect (i.e., thanks to better code coverage) and assess conditionally triggered implicit calls.

Most widely used machine learning potentials for condensed-phase applications rely on many-body permutationally invariant polynomial or atom-centered neural networks. However, these approaches face challenges in achieving chemical interpretability in atomistic energy decomposition and fully matching the computational efficiency of traditional force fields. Here we present a method that combines aspects of both approaches and balances accuracy and force-field-level speed. This method utilizes a monomer-centered representation, where the potential energy is decomposed into the sum of chemically meaningful monomeric energies. The structural descriptors of monomers are described by one-body and two-body effective interactions, enforced by appropriate sets of permutationally invariant polynomials as inputs to the feed-forward neural networks. Systematic assessments of models for gas-phase water trimer, liquid water, methane–water cluster and liquid carbon dioxide are performed. The improved accuracy, efficiency and flexibility of this method have promise for constructing accurate machine learning potentials and enabling large-scale quantum and classical simulations for complex molecular systems.

Aims Lifestyle‐induced weight loss (LIWL) is considered an effective therapy for the treatment of metabolic syndrome (MetS). The role of differentially expressed genes (DEGs) in adipose tissue function and in the success of LIWL in MetS is still unclear. We investigated the effect of 6 months of LIWL on transcriptional regulation in subcutaneous adipose tissue (SAT). Aiming to identify a LIWL‐associated “gene signature” in SAT, DEGs were fitted into a linear regression model. Materials and Methods The study is embedded in a prospective, two‐arm, controlled, monocentric, randomized, 6‐month interventional trial in individuals with MetS following LIWL. The trial included 43 nonsmoking, nondiabetic men aged 45–55 years with MetS. Results In total, we identified 642 DEGs in SAT after 6 months of LIWL. The identified DEGs were validated in two cross‐sectional cohorts analyzing SAT from individuals with and without obesity. Gene enrichment analysis of the DEGs revealed the strongest association with cholesterol metabolic processes. Accordingly, DEGs were correlated with the lipid parameters HDL cholesterol, LDL cholesterol, and triglycerides in corresponding serum samples. We identified 3 genes with an AUC of 0.963 (95% CI: 0.906–1.0) associated with a loss of more than 10% of initial body weight that was maintained for at least 12 months after LIWL, namely SUMO3 (Small ubiquitin‐related modifier 3), PRKG2 (Protein Kinase CGMP‐Dependent 2), and ADAP2 (ArfGAP with Dual PH Domains 2). Conclusion In summary, we have identified DEGs in SAT after LIWL, which may play an important role in metabolic functions. In particular, altered gene expression in SAT may predict sustained weight loss.

Conventional understanding dictates that mammalian neural stem cells (NSCs) exist only in the central nervous system. Here, we report that peripheral NSCs (pNSCs) exist outside the central nervous system and can be isolated from mouse embryonic limb, postnatal lung, tail, dorsal root ganglia and adult lung tissues. Derived pNSCs are distinct from neural crest stem cells, express multiple NSC-specific markers and exhibit cell morphology, self-renewing and differentiation capacity, genome-wide transcriptional profile and epigenetic features similar to control brain NSCs. pNSCs are composed of Sox1⁺ cells originating from neuroepithelial cells. pNSCs in situ have similar molecular features to NSCs in the brain. Furthermore, many pNSCs that migrate out of the neural tube can differentiate into mature neurons and limited glial cells during embryonic and postnatal development. Our discovery of pNSCs provides previously unidentified insight into the mammalian nervous system development and presents an alternative potential strategy for neural regenerative therapy.

The intelligent reconfigurable surface (IRS) is regarded as a highly promising technology for facilitating and enhancing the performance of future wireless communication networks. This is due to its capacity to effectively modify wireless channels in desired destinations with low-cost design and energy consumption. A significant amount of research has been dedicated to exploring the use of conventional IRS, where each phase response element is only connected to its own ground load with no connection to the other phase response elements. However, the simple design of conventional IRS limits its capacity to adjust passive beamforming. This study focuses on the implementation of beyond diagonal IRS (BD-IRS) in multi-carrier non-orthogonal multiple access (NOMA) vehicular communication, surpassing the use of diagonal phase shift matrices. Specifically, we propose a new optimization approach that aims to maximize the achievable spectral efficiency of a multi-carrier NOMA vehicular communication with BD-IRS assistance. This is achieved by optimizing the transmission power of RSU and the phase response of the BD-IRS. We utilize block coordinate descent and successive convex approximation methods to convert the original optimization problem into a series of subproblems. For the power allocation problem at RSU, we adopt Dinkelbach’s and first-order Tayler approximation while exploiting unitary constraint transformation for the phase response problem at BD-IRS and then use the CVX toolbox for the solution. The numerical findings clearly illustrate the advantages of the proposed optimization framework and implementing BD-IRS in multi-carrier NOMA vehicular communications networks in comparison to the conventional IRS architecture.

We study the length of short cycles on uniformly random metric maps (also known as ribbon graphs) of large genus using a Teichmüller theory approach. We establish that, as the genus tends to infinity, the length spectrum converges to a Poisson point process with an explicit intensity. This result extends the work of Janson and Louf to the multi-faced case.

Given the enormous output and pace of development of artificial intelligence (AI) methods in medical imaging, it can be challenging to identify the true success stories to determine the state-of-the-art of the field. This report seeks to provide the magnetic resonance imaging (MRI) community with an initial guide into the major areas in which the methods of AI are contributing to MRI in oncology. After a general introduction to artificial intelligence, we proceed to discuss the successes and current limitations of AI in MRI when used for image acquisition, reconstruction, registration, and segmentation, as well as its utility for assisting in diagnostic and prognostic settings. Within each section, we attempt to present a balanced summary by first presenting common techniques, state of readiness, current clinical needs, and barriers to practical deployment in the clinical setting. We conclude by presenting areas in which new advances must be realized to address questions regarding generalizability, quality assurance and control, and uncertainty quantification when applying MRI to cancer to maintain patient safety and practical utility.

We study the implementability problem for an expressive class of symbolic communication protocols involving multiple participants. Our symbolic protocols describe infinite states and data values using dependent refinement predicates. Implementability asks whether a global protocol specification admits a distributed, asynchronous implementation, namely one for each participant, that is deadlock-free and exhibits the same behavior as the specification. We provide a unified explanation of seemingly disparate sources of non-implementability through a precise semantic characterization of implementability for infinite protocols. Our characterization reduces the problem of implementability to (co)reachability in the global protocol restricted to each participant. This compositional reduction yields the first sound and relatively complete algorithm for checking implementability of symbolic protocols. We use our characterization to show that for finite protocols, implementability is co-NP-complete for explicit representations and PSPACE-complete for symbolic representations. The finite, explicit fragment subsumes a previously studied fragment of multiparty session types for which our characterization yields a co-NP decision procedure, tightening a prior PSPACE upper bound.

This work synthesized ZnO nanoparticles doped and co-doped with Ag and La using a cost-efficient sol–gel method. The structural and morphological features of the nanoparticles were characterized by x-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM). The XRD and FE-SEM confirm the formation of the hexagonal structure of all the synthesized samples. Optical properties were analyzed using UV–visible absorption and photoluminescence spectroscopy. These nanoparticles were subsequently employed as photoanodes in dye-sensitized solar cells (DSSCs). Several configurations of Ag and La doped and co-doped ZnO nanoparticles were tested as photoanodes to assess their impact on device performance. The introduction of Ag and La dopants into ZnO leads to a notable enhancement in the photovoltaic efficiency of the DSSCs. The DSSC incorporating bare ZnO photoanode achieved an efficiency of 0.2554% and on the other hand Ag and La co-doped ZnO photoanode achieved the highest efficiency of 0.9483%, a 271% increase compared to DSSC using undoped ZnO photoanodes. This significant improvement is attributed to the combined effects of Ag and La ions. Ag ions help create a blocking layer that suppresses electron recombination, while La ions enhance light absorption by broadening the spectrum through up/down conversion. The combined effect of Ag and La dopants is responsible for the observed efficiency enhancement in the DSSCs.

The significant challenge of wastewater generation is a global concern that necessitates mitigation through sustainable approaches. Identifying remedies before each unspoiled water reservoir succumbs to contamination resulting from the indiscriminate discharge of wastewater is crucial. Constructed wetlands integrated bio-electrochemical technologies (CW-BES) stand out as a recently devised sustainable technology that holds promise in addressing the challenge of wastewater treatment while concurrently facilitating the recovery of bioelectricity as a secondary byproduct. This chapter extensively delves into the intricacies of CW-BES, exploring their development, fundamental electron transfer mechanisms, various configurations such as constructed wetland integrated microbial fuel cells (CW-MFCs), MET lands, or electroactive wetlands employed to date, the diverse range of media/electrodes utilized, as well as the identified microbial diversification. The focus extends to comprehensively understanding the factors influencing CW-BES performance. Further, the chapter highlights the practical feasibility of deploying such sustainable technology in real-world applications on a larger commercial scale and the challenges associated with their implementation and operation. Finally, a techno-economic assessment of CW-BES technologies is discussed to evaluate the economic feasibility of scaling up these systems.

Amyotrophic lateral sclerosis is an incurable neurodegenerative disease that is fatal with a median of 3–4 years. It is characterized by degeneration of the first and second motor neurons. In addition to physical limitations, neuropsychological abnormalities occur in more than 50% of cases. This leads to a rapid loss of autonomy and increases the need for care. An individual prognosis for the course of the disease, in particular the development of cognitive and behavioural abnormalities, is not yet possible As part of our investigations, we focused on cognitive performance and behavioural abnormalities measured by the Edinburgh Cognitive and Behavioural ALS Screen in patients with amyotrophic lateral sclerosis and investigated possible prognostic biomarkers in cerebrospinal fluid as well as modifiable factors such as nutrition and lung function. A retrospective data analysis of 99 patients with amyotrophic lateral sclerosis cases examined between 2018 and 2021 at the Department for Neurodegenerative Diseases and Gerontopsychiatry at the University Hospital of Bonn, using Edinburgh Cognitive and Behavioural ALS Screen, revealed that elevated levels of total tau and phospho-tau 181 were associated with diminished performance of patients with amyotrophic lateral sclerosis on the Edinburgh Cognitive and Behavioural ALS Screen. Additionally, weight loss during the course of the disease has been observed to have a deleterious impact on cognitive performance. Moreover, we were able to demonstrate a previously insufficiently described correlation between abnormalities in the Edinburgh Cognitive and Behavioural ALS Screen and low-normal thiamine levels in serum. The hypothesis that reduced lung function has a negative effect on cognitive performance was not supported by our findings. The initial onset of amyotrophic lateral sclerosis, whether bulbar or spinal, does not appear to affect cognition and behaviour measured using Edinburgh Cognitive and Behavioural ALS Screen. Furthermore, our findings confirm the utility of the Edinburgh Cognitive and Behavioural ALS Screen in identifying a behavioural variant frontotemporal dementia in amyotrophic lateral sclerosis patients who have been previously diagnosed by experienced neurologists using the Rascovsky criteria. This development facilitates a more precise utilization of complex diagnostic instruments. Our results provide insight into the prognosis of patients with amyotrophic lateral sclerosis in terms of cognitive performance and behavioural abnormalities as the disease progresses, as well as potential therapeutic approaches to stabilize and support neuropsychological abnormalities. The importance of total tau as a widely available prognostic marker should be emphasized. Additionally, new avenues of research are emerging, particularly regarding the role of thiamine in amyotrophic lateral sclerosis.

One of Earth’s largest carbon fluxes is driven by particles made from photosynthetically fixed matter, which aggregate and sink into the deep ocean. While biodegradation is known to reduce this vertical flux, the biophysical processes that control particle sinking speed are not well understood. Here, we use a vertical millifluidic column to video-track single particles and find that biogels scavenged by particles during sinking significantly reduce the particles’ sinking speed, slowing them by up to 45% within one day. Combining observations with a mathematical model, we determine that the mechanism for this slowdown is a combination of increased drag due to the formation of biogel tendrils and increased buoyancy due to the biogel’s low density. Because biogels are pervasive in the ocean, we propose that by slowing the sinking of organic particles they attenuate the vertical carbon flux in the ocean.