University of Luxembourg

In this paper, we investigate a secure transmission for a rate-splitting multiple-access (RSMA)-based multiple-input single-output (MISO) underlay cognitive radio (CR) system. The proposed network is composed of a set of secondary users (SUs) that utilize simultaneous wireless information and power transfer (SWIPT) technology and an additional set of non-linear energy harvesting (EH) users. Moreover, the system model under consideration is exposed to multiple eavesdroppers. Thus, we propose to minimize the transmit power intended to the SUs and EH users while maximizing the artificial noise (AN) generated by the secondary transmitter, aiming to counter eavesdroppers’ wiretaps while satisfying the quality-of-service constraints. Therefore, we develop a novel approach based on ant colony regression (ACOR) and semidefinite relaxation (SDR) methods to solve the challenging and non-convex problem which is further transformed into a bilevel optimization problem. Afterward, we investigate a comparative solution based on the particle swarm optimization (PSO) algorithm, the successive convex approximation (SCA) technique, and analyze the incidence of linear and non-linear EH designs. In addition, we compare the RSMA-based scheme with non-orthogonal multiple-access (NOMA), space-division multiple access (SDMA), and zero-forcing (ZF) techniques. Satisfactorily, simulation results prove the proposed ACOR-SDR framework achieves better performance and lower complexity than its counterparts.

In recent years, a growing number of contributions on green finance have emerged, not only within economic geography but also increasingly from disciplines beyond it. With this Special Issue, we aim to engage with the ongoing debate around green and sustainable finance and its challenges, including concerns over greenwashing. Our extended editorial provides structure to this complex discussion by identifying four primary strands of literature that frame the field. Two of these strands adopt a more critical stance, combining analytical approaches and rigorous assessments that question the impact and ‘authenticity’ of green and sustainable finance schemes, approaches and policies. Most of the contributions and empirical case studies featured here align with these critical perspectives, which are introduced in greater depth in the second part of this editorial.

Background Neurodegenerative disorders, including Alzheimer’s disease (AD), have been linked to alterations in tryptophan (TRP) metabolism. However, no studies to date have systematically explored changes in the TRP pathway at both transcriptional and epigenetic levels. This study aimed to investigate transcriptomic, DNA methylomic (5mC) and hydroxymethylomic (5hmC) changes within genes involved in the TRP and nicotinamide adenine dinucleotide (NAD) pathways in AD, using three independent cohorts. Methods DNA derived from post-mortem middle temporal gyrus (MTG) tissue from AD patients (n = 45) and age-matched controls (n = 35) was analyzed, along with DNA derived from blood samples from two independent cohorts: the German Study on Ageing, Cognition, and Dementia in Primary Care Patients (AgeCoDe) cohort (n = 96) and the Dutch BioBank Alzheimer Center Limburg (BBACL) cohort (n = 262). Molecular profiling, including assessing mRNA expression and DNA (hydroxy)methylation levels, was conducted using HumanHT-12 v4 Expression BeadChip and HM 450 K BeadChip arrays, respectively. Functional interactions between genes and identification of common phenotype-specific positive and negative elementary circuits were conducted using computational modeling, i.e. gene regulatory network (GRN) and network perturbational analysis. DNA methylation of IDO2 (cg11251498) was analyzed using pyrosequencing. Results Twelve TRP- and twenty NAD-associated genes were found to be differentially expressed in the MTG of AD patients. Gene sets associated in the kynurenine pathway, the most common TRP pathway, and NAD pathway, showed enrichment at the mRNA expression level. Downstream analyses integrating data on gene expression, DNA (hydroxy)methylation, and AD pathology, as well as GRN and network perturbation analyses, identified IDO2, an immune regulatory gene, as a key candidate in AD. Notably, one CpG site in IDO2 (cg11251498) exhibited significant methylation differences between AD converters and non-converters in the AgeCoDe cohort. Conclusion These findings reveal substantial transcriptional and epigenetic alterations in TRP- and NAD-pathway-associated genes in AD, highlighting IDO2 as a key candidate gene for further investigation. These genes and their encoded proteins hold potential as novel biomarkers and therapeutic targets for AD.

Due to their flexibility, Fox-H functions are widely studied and applied to many research topics, such as astrophysics, statistical mechanics, and probability. Well-known special cases of Fox-H functions, such as Mittag-Leffler and Wright functions, find a wide application in the theory of stochastic processes, anomalous diffusions and non-Gaussian analysis. In this paper, we focus on certain explicit assumptions that allow us to use the Fox-H functions as densities. We then provide a subfamily of the latter, called Fox-H densities with all moments finite, and give their Laplace transforms as entire generalized Wright functions. The class of random variables with these densities is proven to possess a monoid structure. We present eight subclasses of special cases of such densities (together with their Laplace transforms) that are particularly relevant in applications, thanks to their probabilistic interpretation. To analyze the existence conditions of Fox-H functions as well as their sign, we derive asymptotic results and their analytic extension.

Objective Neuronal cell death and neuroinflammation are characteristic features of epilepsy, but it remains unclear whether neuronal cell death as such is causative for the development of epileptic seizures. To test this hypothesis, we established a novel mouse line permitting inducible ablation of pyramidal neurons by inserting simian diphtheria toxin (DT) receptor (DTR) cDNA into the Ccl17 locus. The chemokine CCL17 is expressed in pyramidal CA1 neurons in adult mice controlling microglial quiescence. Methods Seizure activity in CCL17‐DTR mice was analyzed by electroencephalographic recordings following treatment with DT for 3 consecutive days. Neuroinflammation and neuronal cell death were evaluated by (immuno)histochemistry. Pharmacological inhibition of TNFR1 signaling was achieved by treatment with XPro1595, a dominant‐negative inhibitor of soluble tumor necrosis factor. Results Neuronal cell death was detectable 7 days (d7) after the first DT injection in heterozygous CCL17‐DTR mice. Spontaneous epileptic seizures were observed in the vast majority of mice, often with an initial peak at d6–9, followed by a period of reduced activity and a gradual increase during the 1‐month observation period. Microglial reactivity was overt from d5 after DT administration not only in the CA1 region but also in the CA2/CA3 area, shortly followed by astrogliosis. Reactive microgliosis and astrogliosis persisted until d30 and, together with neuronal loss and stratum radiatum shrinkage, reflected important features of human hippocampal sclerosis. Granule cell dispersion was detectable only 3 months after DT treatment. Application of XPro1595 significantly reduced chronic seizure burden without affecting the development of hippocampal sclerosis. Significance In conclusion, our data demonstrate that sterile pyramidal neuronal death is sufficient to cause epilepsy in the absence of other pathological processes. The CCL17‐DTR mouse line may thus be a valuable model for further mechanistic studies on epilepsy and assessment of antiseizure medication.

In orthogonal frequency division multiplexing (OFDM)-based dual-function radar-communication (DFRC) systems, achieving low peak-to-average power ratio (PAPR) is essential for transmission efficiency and performance. Traditional PAPR constraints, however, fall short in managing the dynamic range of waveforms, thereby limiting power maximization. This study introduces a peak-to-valley power ratio (PVPR) constraint for multiple-input multiple-output (MIMO) DFRC systems to enhance hardware compatibility, waveform fidelity, and consistent transmission power. We develop low-PVPR OFDM waveforms tailored for MIMO-DFRC systems, improving both radar and communication functions. For radar applications, we optimize the weighted peak or integrated sidelobe level (WPISL) and employ phase-encoded waveforms to minimize sidelobes. For communication purposes, we implement a constructive interference (CI) design coupled with a waveform similarity error (WSE) constraint. Utilizing the majorization-minimization (MM) framework, we convert the non-convex problem into a series of convex ones. Numerical results demonstrate significant improvements in sidelobe reduction, symbol error rate (SER), and average achievable rate, thereby validating the effectiveness of our approach in enhancing DFRC systems.

When using database management systems (DBMSs), it is common to distribute instance replicas across multiple locations for disaster recovery and scaling purposes. To efficiently geo-replicate data, it is crucial to ensure the data and its replicas remain consistent with the same and the most up-to-date data. However, DBMSs’ inner characteristics and external factors, such as the replication strategy and network latency, can affect system performance when dealing with data replication, especially when the replicas are deployed far apart from the others. Thus, it is essential to comprehend how achieving high data consistency levels in geo-replicated systems can impact systems performance. This work analyzes various data consistency settings for the widely used NoSQL DBMSs, namely MongoDB, Redis, and Cassandra. The analysis is based on real-world experiments in which DBMS nodes are deployed on cloud platforms in different locations, considering single and multiple region deployments. Based on the results of the experiments, we provide a comprehensive analysis regarding the system throughput and response time when executing reading and writing operations, pointing out scenarios where each DBMS could be better employed. Some of our findings include, for instance, that opting for strong data consistency significantly impacts Cassandra’s reading operations in the single-region deployment, while MongoDB writing operations are most affected in a multi-region scenario. Additionally, all of these DBMSs exhibit statistically significant variations across all scenarios in the multi-region setup when the data consistency is switched from weak to stronger level.

Allergen-specific immunotherapy (AIT) induces immune tolerance, showing the highest success rate (>95%) for insect venom while a much lower chance for pollen allergy. However, the molecular switches leading to successful durable tolerance restoration remain elusive. The primary outcome of this observational study is the comprehensive immunological cellular characterization during the AIT initiation phase, whereas the secondary outcomes are the serological and Th2-cell-type-specific transcriptomic analyses. Here we apply a multilayer-omics approach to reveal dynamic peripheral immune landscapes during the AIT-initiation phase in venom allergy patients (VAP) versus pollen-allergic and healthy controls. Already at baseline, VAP exhibit altered abundances of several cell types, including classical monocytes (cMono), CD4⁺ hybrid type 1-type 17 cells (Th1-Th17 or Th1/17) and CD8⁺ counterparts (Tc1-Tc17 or Tc1/17). At 8-24 h following AIT launch in VAP, we identify a uniform AIT-elicited pulse of late-transitional/IL-10-producing B cells, IL-6 signaling within Th2 cells and non-inflammatory serum-IL-6 levels. Sequential induction of activation and survival protein markers also immediately occur. A disequilibrium between serum IL-6 and cMono in VAP baseline is restored at day seven following AIT launch. Our longitudinal analysis discovers molecular switches during initiation-phase insect-venom AIT that secure long-term outcomes. Trial number: NCT02931955.

This study examined the sex-related variation in the developmental changes of maximal short-term power outputs in young Brazilian volleyball athletes while considering the potential influence of body size. The study included 75 participants, comprising 35 females and 40 males aged between 10.5 and 17.8 years. Performance assessment included the countermovement jump, 10 m sprint, 2 kg medicine ball throw and volleyball-specific agility. Athletes were measured 3–4 times over 12 months. Bayesian hierarchical models were used to model developmental trends across adolescence. The results revealed substantial developmental improvements in maximal short-term power outputs during adolescence, with particularly noteworthy advancements observed among male athletes. Our model predictions revealed a pronounced non-linear increase in jumping and sprint performance at around ages 14 and 16 years for females and males, respectively; however, further improvements plateaued once these peak levels were attained, resulting in negligible gains. Female athletes displayed a markedly lower rate of development in the 2 kg medicine ball throw compared to male athletes. Conversely, there were no sex-based differences in the rate of linear performance improvement in the volleyball-specific agility test. These findings offer valuable insights to coaches, helping them better comprehend the asynchrony in the progression of volleyball-specific maximal short-term power outputs during adolescence.

Background. In the Compensatory-Dissociative Online Gaming (C-DOG; Giardina et al., 2024) model, we proposed a continuum from compensatory to dissociative gaming involvement. This continuum represents different degrees of integration between physical and virtual environments with three core processes – Active Escapism, Escape, and Dissociation – and two peripheral processes – Gaming-Related Relaxation and Body-Mind Detachment. Here, we developed and tested a multidimensional measure based on this model. Methods. We capitalized on existing items for measuring escapism and dissociation and we generated new items consistent with the hypothesized model dimensions. A total of 54 items were administered to 1,176 online gamers playing different game genres, together with measures of problematic gaming, passion for gaming, and other psychological distress indicators. Results. Exploratory and confirmatory factor analyses yielded a six-factor, 36-item structure, with multiple hierarchical regression analyses highlighting unique associations with other psychological constructs assessed. Discussion. The following factors were identified: (1) Emotional Displacement - redirection of negative emotion into the game with associated relaxation; (2) Absorption - detachment of the player from time and space while gaming; (3) Active Escapism - simulative use of the game to compensate for lack of self-confidence in reaching physical life objectives; (4) Virtual Withdrawal – maladaptive gaming to balance impaired social functioning, predicted by traumatic experiences and pervasive depression; (5) Dissociative Regulation - dysfunctional level of engagement associated with excessive anxiety; (6) Failure Escape - problematic avoidance via gaming related to fear of future failures. Conclusions. The C-DOG factors identify critical psychological processes associated with problematic gaming, with relevant research and clinical implications.

We study the effect of using high-resolution elevation data on the selection of the most fuel-efficient (greenest) path for different trucks in various urban environments. We adapt a variant of the Comprehensive Modal Emission Model (CMEM) to show that the optimal speed and the greenest path are slope dependent (dynamic). When there are no elevation changes in a road network, the most fuel-efficient path is the shortest path with a constant (static) optimal speed throughout. However, if the network is not flat, then the shortest path is not necessarily the greenest path, and the optimal driving speed is dynamic. We prove that the greenest path converges to an asymptotic greenest path as the payload approaches infinity and that this limiting path is attained for a finite load. In a set of extensive numerical experiments, we benchmark the $\hbox {CO}_{2}$ emissions reduction of our dynamic speed and the greenest path policies against policies that ignore elevation data. We use the geo-spatial data of 25 major cities across 6 continents. We observe numerically that the greenest path quickly diverges from the shortest path and attains the asymptotic greenest path even for moderate payloads. Based on an analysis of variance, the main determinants of the $\hbox {CO}_{2}$ emissions reduction potential are the variation of the road gradients along the shortest path as well as the relative elevation of the source from the target. Using speed data estimates for rush hour in New York City, we test $\hbox {CO}_{2}$ emissions reduction by comparing the greenest paths with optimized speeds against the fastest paths with traffic speed. We observe that selecting the greenest paths instead of the fastest paths can significantly reduce $\hbox {CO}_{2}$ emissions. Additionally, our results show that while speed optimization on uphill arcs can significantly help $\hbox {CO}_{2}$ reduction, the potential to leverage gravity for acceleration on downhill arcs is limited due to traffic congestion.

As one cannot know in advance where a crack will form, currently used discrete crack monitors may miss to detect a crack if it grows outside the monitored regions. A high-resolution continuous 2D strain monitor applied to the entire surface of interest would solve this problem. Cholesteric liquid crystal elastomers (CLCEs) provide this ability, and with recent advances in chemistry, they can be applied very easily, similar to a paint coating. Here we demonstrate the detection of new cracks and monitoring of their progression using CLCE coatings applied to an extruded polystyrene insulation panel, an aerated concrete brick, and a reinforced concrete beam, respectively. Regardless of where and in which direction a crack develops, it can be easily detected thanks to a change in color. By analyzing the new color, quantitative information on the crack width can be extracted. Considering the ease of applying the CLCEs to standard building materials, the high 2D resolution strain monitoring with clear optical detection that it provides, and the low cost of the solution, we argue that CLCE coatings can have a revolutionary impact on structural health monitoring for buildings and infrastructure, to be constructed or already existing.

Parkinson’s disease, an aging-associated neurodegenerative disorder, is characterised by nigrostriatal pathway dysfunction caused by the gradual loss of dopaminergic neurons in the substantia nigra pars compacta of the midbrain. Human in vitro models are enabling the study of the dopaminergic neurons’ loss, but not the dysregulation within the dopaminergic network in the nigrostriatal pathway. Additionally, these models do not incorporate aging characteristics which potentially contribute to the development of Parkinson’s disease. Here we present a nigrostriatal pathway model based on midbrain-striatum assembloids with inducible aging. We show that these assembloids can develop characteristics of the nigrostriatal connectivity, with catecholamine release from the midbrain to the striatum and synapse formation between midbrain and striatal neurons. Moreover, Progerin-overexpressing assembloids acquire aging traits that lead to early neurodegenerative phenotypes. This model shall help to reveal the contribution of aging as well as nigrostriatal connectivity to the onset and progression of Parkinson’s disease.

In their study, Stavropoulos et al. (2023) capitalized on supervised machine learning and a longitudinal design and reported that the User-Avatar Bond could be accurately employed to detect Gaming Disorder (GD) risk in a community sample of gamers. The authors suggested that the User-Avatar Bond is a “digital phenotype” that could be used as a diagnostic indicator for GD risk. In this commentary, our objectives are twofold: (1) to underscore the conceptual challenges of employing User-Avatar Bond for conceptualizing and diagnosing GD risk, and (2) to expound upon what we perceive as a misguided application of supervised machine learning techniques by the authors from a methodological standpoint.

The layered structure of smectic liquid crystals cannot develop unobstructed when confined to spherical shells with layers extending in the radial direction, since the available cross section area increases from the inside to the outside of the shell yet the number and thickness of layers must be constant. For smectic-A (SmA) liquid crystals, with the layer normal m parallel to the director n, the frustration breaks up the texture into spherical lune domains with twist deformations of alternating sense, overlaid with a herringbone-like secondary modulation and mediated via localized bend regions where the boundary conditions are violated. The SmC phase has more degrees of freedom to resolve the frustration thanks to its non-zero tilt angle τ between n and m, but its response to tangential shell confinement was never studied. We show experimentally and theoretically that the lunes in shells undergoing a SmA-SmC transition become twice as wide and half as many and they lose the secondary modulation, adopting a configuration with no layer twist but uniform layer bend if τ reaches a large enough value. Our study expands our understanding of how smectics respond to spherical confinement and it opens new soft matter research opportunities, given the rich diversity of phases with SmC-like symmetry, including chiral and spontaneously polarized phases.

Fibrillary aggregation of α-synuclein in Lewy body inclusions and nigrostriatal dopaminergic neuron degeneration define Parkinson’s disease neuropathology. Mutations in GBA1, encoding glucocerebrosidase, are the most frequent genetic risk factor for Parkinson’s disease. However, the lack of reliable experimental models able to reproduce key neuropathological signatures has hampered the clarification of the link between mutant glucocerebrosidase and Parkinson’s disease pathology. Here, we describe an innovative protocol for the generation of human induced pluripotent stem cell-derived midbrain organoids containing dopaminergic neurons with nigral identity that reproduce characteristics of advanced maturation. When applied to patients with GBA1-related Parkinson’s disease, this method enabled the differentiation of midbrain organoids recapitulating dopaminergic neuron loss and fundamental features of Lewy body pathology observed in human brains, including the generation of α-synuclein fibrillary aggregates with seeding activity that also propagate pathology in healthy control organoids. Still, we observed that the retention of mutant glucocerebrosidase in the endoplasmic reticulum and increased levels of its substrate glucosylceramide are determinants of α-synuclein aggregation into Lewy body-like inclusions. Consistently, the reduction of glucocerebrosidase activity accelerated α-synuclein pathology by promoting fibrillary α-synuclein deposition. Finally, we demonstrated the efficacy of ambroxol and GZ667161 – two modulators of the glucocerebrosidase pathway in clinical development for the treatment of GBA1-related Parkinson’s disease – in reducing α-synuclein pathology in this model, supporting the use of midbrain organoids as a relevant pre-clinical platform for investigational drug screening.