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One of the promising opportunities of digital health is its potential to lead to more holistic understandings of diseases by interacting with the daily life of patients and through the collection of large amounts of real-world data. Validating and benchmarking indicators of disease severity in the home setting is difficult, however, given the large number of confounders present in the real world and the challenges in collecting ground truth data in the home. Here we leverage two datasets collected from patients with Parkinson's disease, which couples continuous wrist-worn accelerometer data with frequent symptom reports in the home setting, to develop digital biomarkers of symptom severity. Using these data, we performed a public benchmarking challenge in which participants were asked to build measures of severity across 3 symptoms (on/off medication, dyskinesia, and tremor). 42 teams participated and performance was improved over baseline models for each subchallenge. Additional ensemble modeling across submissions further improved performance, and the top models validated in a subset of patients whose symptoms were observed and rated by trained clinicians.

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement is an action over a system that limits its units’ translational and rotational degrees of freedom, thus also influencing the system’s phase space probability density; it can function as either a catalyst or inhibitor of self-organisation. Confinement can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework and perspective for future research, we examine the role of confinement in the self-organisation of soft-matter systems and identify overarching scientific challenges that need to be addressed to harness its full scientific and technological potential in soft matter and related fields. By drawing analogies with other disciplines, this framework will accelerate a common deeper understanding of self-organisation and trigger the development of innovative strategies to steer it using confinement, with impact on, e.g., the design of smarter materials, tissue engineering for biomedicine and in guiding active matter.

The Digital Markets Act (DMA) constitutes a crucial part of the European legislative framework addressing the dominance of 'Big Tech'. It intends to foster fairness and competition in Europe's digital platform economy by imposing obligations on 'gatekeepers' to share end-user-related information with business users. Yet, this may involve the processing of personal data subject to the General Data Protection Regulation (GDPR). The obligation to provide access to personal data in a GDPR-compliant manner poses a regulatory and technical challenge and can serve as a justification for gatekeepers to refrain from data sharing. In this research-in-progress paper, we analyze key tensions between the DMA and the GDPR through the paradox perspective. We argue through a task-technology fit approach how privacy-enhancing technologies-particularly anonymization techniques-and portability could help mediate tensions between data sharing and privacy. Our contribution provides theoretical and practical insights to facilitate legal compliance.

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. Consequently, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated.We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion channel families. We collected and curated 3,049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12,546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures.We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis center and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate (NMDA) receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1,422 neurodeve

This paper introduces the concept of multi-connectivity (MC) to the multi-orbit non-terrestrial networks (NTNs), where user terminals can be served by more than one satellite to achieve higher peak throughput. MC is a technique initially introduced by the 3rd Generation Partnership Project (3GPP) for terrestrial communications in 4G and 5G, it has shown much gain in the terrestrial domain and this paper explores areas where this concept can benefit the satellite domain. MC can increase throughput, but this entails increased power consumption at user terminal for uplink transmissions. The energy efficiency of uplink communications can be improved by designing efficient scheduling schemes, and to this end, we developed a terminal aware multi-connectivity scheduling algorithm. This proposed algorithm uses the available radio resources and propagation information to intelligently define a dynamic resource allocation pattern, that optimally routes traffic so as to maximize uplink data rate while minimizing the energy consumption at the UT. The algorithm operates with the terminal differentiating multi-layer NTN resource scheduling architecture, which has a softwarized dispatcher at the network layer that classifies and differentiates the packets based on terminal type. The performance of the proposed algorithm was compared with round robin and joint carrier schedulers in terms of uplink data rate and energy efficiency. We also provide architectural design of implementable schedulers for multi-orbital satellite networks that can operate with different classes of terminals.

Like most school subjects and their respective mother sciences and research areas, physical education faces severe challenges caused by recent political and social developments. Due to the implementation of international guidelines and increased immigration, inclusion and intercultural learning, as well as corresponding teacher training, will be critical issues for the educational sciences in general and for physical education in particular. This applies also to the use of new information and communication technology. How, how often, under what conditions and for what purpose should tools such as tablets, software apps and activity trackers be used by physical education teachers and other physical activity educators and practitioners? What are the benefits and the risks? However, the most relevant problem the field of physical education and physical activity is currently confronted with is the changing physical activity behaviour of children and youth, particularly in developed countries. A joint effort of researchers, educationalists, politicians, and teachers is needed to determine the causes of young people’s physical inactivity and develop effective strategies and programmes that can be implemented in school as well as community settings in general. At the 4th CIAPSE Congress in Luxembourg, leading researchers and educationalists from all over Europe addressed these challenges and developments and presented innovative concepts. The main topics and sub-themes were: - The Promotion of Physical Activity and Play in Children - Physical Literacy in Children - Physical Education in Early Childhood and Primary Education - Physical Education Teacher Education in Early Childhood and Primary Education - Physical Activity in Active School Settings - Physical Activity for Health Promotion and Active Community in a Sustainable and Healthy World - Intercultural Learning, Diversity and Inclusion in Physical Education and Physical Activity - Physical Education, Physical Activit

Neurodevelopmental disorders (NDDs), including severe pediatric epilepsy, autism, and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are ‘Variants of Uncertain Significance’. To safely enroll patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can ‘tolerate’ missense variants and which ones are ‘essential’ and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the three-dimensional (3D) structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14,377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360,000 NDD

This work surveys mathematical aspects of division property, which is a state of the art technique in cryptanalysis of symmetric-key algorithms, such as authenticated encryption, block ciphers and stream ciphers. It aims to find integral distinguishers and cube attacks, which exploit weakness in the algebraic normal forms of the output coordinates of the involved vectorial Boolean functions. Division property can also be used to provide arguments for security of primitives against these attacks. The focus of this work is a formal presentation of the theory behind the division property, including rigorous proofs, which were often omitted in the existing literature. This survey covers the two major variants of division property, namely conventional and perfect division property. In addition, we explore relationships of the technique with classic degree bounds

Accurate user equipment (UE) localization in an obstacle-dense environment is quite challenging due to the insufficiency of line-of-sight (LoS) links. However, the reconfigurable intelligent surface (RIS) has the potential for offering alternative RIS-assisted LoS links to refine the localization results. In this paper, a recursive localization scheme is proposed based on an iterative RIS selection strategy, with the help of prior knowledge of the propagation environment. And numerical results based on a geometry-based channel simulator in a typical composite urban environment exhibit the improvement of localization accuracy.

Walking meetings are a promising way to reduce unhealthy sedentary behavior at the office. Some aspects of walking meetings are however hard to assess using traditional research approaches that do not account well for the embodied experience of walking meetings. We conducted a series of 16 bodystorming sessions, featuring unusual walking meeting situations to engage participants (N=45) in a reflective experience. After each bodystorming, participants completed three tasks: a body map, an empathy map, and a rating of workload using the NASA-TLX scale. These embodied explorations provide insights on key themes related to walking meetings: material and tools, physical and mental demand, connection with the environment, social dynamics, and privacy. We discuss the role of technology and opportunities for technology-mediated walking meetings. We draw implications for the design of walking meeting technologies or services to account for embodied experiences, and the individual, social, and environmental factors at play.

Steel wire ropes are used for numerous industrial applications such as ships, elevators, cranes and bridges. A wire rope consists of numerous thin, steel wires and its geometrical construction can be explained in two steps. First, several wires are wrapped together in a helical shape called a strand. Second, several strands are wrapped together in a helical shape to form the final wire rope. In most cases, each strand is compacted before they are wrapped together to form the final wire rope. Compaction generally reduces contact stresses and thereby, extends ropes’ service life. Not many models have been proposed to predict the compaction process and its influence on the strand’s mechanical behavior during service. This contribution proposes a computationally efficient approach that consists of two elastoplastic mechanical models. The first model, describing the compaction process, is of a 2D plane strain nature and is therefore fast. Subsequently, the 2D geometry and plastic variables predicted by the compaction model are used to generate the initial geometry and initial plastic state of a 3D model, that is subsequently used to describe the strand’s mechanical behavior during service (we limit ourselves to tension). The results of the approach, with and without the mapping of the plastic variables, are compared to experimental measurements and the results without compaction. This is investigated for two real world strands.

The papers of this special issue investigate the persistent challenges to European Banking Union and explore the tensions between broader financial stability objectives and national political and socio-economic pressures through a diversity of lenses. In this introduction, we examine two main issues that need to be addressed in order to strengthen Banking Union: the incomplete institutional design of Banking Union and the difficulties encountered in applying the different elements of Banking Union to loosen sovereign-bank ties. These elements include the so-called ‘single’ rulebook, supervision, resolution, and financial mechanisms to support and resolve banks.

Instructional quality in Human-Computer Interaction (HCI) education is crucial to ensure that students acquire the necessary skills to understand the complexity of socio-technical systems and design interfaces and interactions accordingly. Previous empirical evidence suggests that teaching quality is determined by teacher knowledge – domain-specific, pedagogical, and technological knowledge. Through a survey of N=54 HCI instructors, this paper reports on teacher knowledge and investigates its relationship with their perceived teaching quality at different levels of HCI education. Findings show that HCI instructors rated their domain-specific and technological knowledge rather high, while the components of pedagogical knowledge were rated lower. Yet, pedagogical knowledge was related to instructional quality, specifically the degree of cognitive activation provided to students. We contribute by documenting and discussing the strengths and weaknesses of HCI instructors’ knowledge and teaching quality. We draw implications for instructors, institutions and the HCI education community.

Inaudible syntactic markers are especially difcult to spell. This paper examines how 455 fourth graders spell silent French plural markers in a dictation with real and pseudowords after one year of formal French instruction (L2). The Generalized Linear Mixed Model analysis shows frst that noun plural spelling (real and pseudo) is a strong predictor for verb and adjective plural spelling. Second, the performance on real verb plural is higher than the performance on real adjective plural. In con‑ trast, the performance on pseudoadjective plural is higher than on pseudoverb plural. Our fndings indicate the strong infuence of semantics and frequency in instruction input on plural spelling: noun plural is semantically grounded, and nouns are most frequent in the curriculum. Verbs and verb plural are also frequent, and infection is mostly taught by means of memorizing the verb infection paradigm. Adjectives are taught least frequently. The fndings are discussed in the context of French L2 instruction, as the extremely low results on adjectives and pseudoverbs seem to be a consequence of instruction methods.

Albeit recent technological developments (e.g. field deployable instruments operating at high temporal frequencies), experimental hydrology is a discipline that remains measurement limited. From this perspective, trans-disciplinary approaches may create valuable opportunities to enlarge the number of tools available for investigating hydrological processes. Tracing experiments are usually performed in order to investigate the water flow pathways and water sources in underground areas. Since the 19th century, researchers have worked with hydrological tracers to do this. Among them, the fluorescent dyes and the isotopes are the most commonly used to follow the water flow while others like salts or bacteriophages are employed as additional tracers to those mentioned above. Bacteriophages are the least known of all, but it has been studied since the 1960s as hydrological tracers, especially in karstic environments. The purpose is to evaluate the potential for bacteriophages naturally occurring in soils to serve as a new environmental tracer of hydrological processes. We hypothesize that such viral particles can be a promising tool in water tracing experiments since they are safe for ecosystems. In both fields of hydrology and virology, the knowledge regarding the fate of bacteriophages within the pedosphere is still limited. Their study would not only allow proposing potential new candidates to enlarge the hydrological tracers available, but also improving the current knowledge about the bacteriophage communities in soil and their interactions with certain environmental factors. For this purpose, we aim at describing the bacteriophage communities occurring in the soil through shotgun metagenomics analysis. Those viruses are widely spread in the pedosphere, and we assume that they have specific signatures according to the type of soil. Then, bacteriophage populations will be investigated in the soil water to analyse the dis/similarities between the two communities as wel

Climate change has increased the frequency and intensity of weather events with heavy precipitation, making communities worldwide more vulnerable to flash flooding. As a result, accurate fore- and nowcasting of impending excessive rainfall is crucial for warning and mitigating these hydro-meteorological hazards. The measurement of integrated water vapour along slant paths is made possible by ground-based global positioning system (GPS) receiver networks, delivering three-dimensional (3D) water vapour distributions at low cost and in real-time. As a result, these data are an invaluable supplementary source of knowledge for monitoring storm events and determining their paths. However, it is generally known that multipath effects at GPS stations have an influence on incoming signals, particularly at low elevations. Although estimates of zenith total delay and horizontal linear gradients make up the majority of the GPS products for meteorology to date, these products are not sufficient for understanding the full 3D distribution of water vapour above a station. Direct utilization of slant delays can address this lack of azimuthal information, although, at low elevations it is more prone to multipath (MP) errors. This study uses the convective storm event that happened on 27 July 2017 over Bulgaria, Greece, and Turkey, which caused flash floods and severe damage, to examine the effects of multipath-corrected slant wet delay (SWD) estimations on monitoring severe weather events. First, we reconstructed the one-way SWD by adding GPS post-fit phase residuals, describing the anisotropic component of the SWD. Because MP errors in the GPS phase observables can considerably impact SWD from individual satellites, we used an averaging technique to build station-specific MP correction maps by stacking the post-fit phase residuals acquired from a precise point positioning (PPP) processing strategy. The stacking was created by spatially organizing the residuals into congruent cells w

CubeSats constellations using commercial off-the-shelf components have been studied for different applications, such as GNSS Radio Occultation (GNSS-RO). Furthermore, precise orbit determination of Low Earth Orbit (LEO) CubeSats based on multiple GNSS constellations would open new opportunities for scientific applications such as Earth’s gravity field measurements. In GNSS kinematic orbit determination, which is the common method used for small sats, the derived orbits are affected by noise, data gaps, outliers, measurement errors as well as poor geometry of the observations. Our work seeks to mitigate these issues and we present two areas of research: 1) GNSS network processing of GPS and Galileo constellations and 2) kinematic orbit determination of a set of Spire CubeSats that host a GNSS-RO payload. An initial architecture of kinematic orbit processing for the Spire GNSS-RO CubeSats constellation is obtained and the details on validations and limitations are discussed in more details. In addition, we showcase the agreement between the GNSS orbit products produced at the University of Luxembourg (UL) with those of the Center for Orbit Determination in Europe (CODE). Finally, the Spire kinematic orbits based on the raw observation approach are derived and compared to the L1B Spire orbit products.

Purpose The purpose of this paper is to explore the perception of the mental health problems of the homeless population in a high-income country (Luxembourg) by social service providers and to develop proposals for better inclusion of homeless people into the mental health services and homeless people with mental health issues into society. Design/methodology/approach The study was of qualitative design and conducted using a semi-structured interview method (in person). The semi-structured interviews (seven participants) were conducted to analyse the challenges, practice approaches and prospects of stakeholders or decision-makers working in housing exclusion and homelessness. A secondary thematic analysis of this content regarding mental health issues was performed. Findings Three main themes in the social providers’ perception were identified related to mental health and homelessness: the general view on the mental health problems of homeless people (accent on substance use disorders [SUDs], overshadowing of other mental health conditions by the SUDs); the positive impact of housing and social services on the mental health of the homeless per se (role of social rhythms, social connectedness and multidisciplinary approach are emphasised); and the need for improvement of mental health services in the country (need for the long-term timely continuing mental health support and recognition of the importance of complex intersectional and multidisciplinary solutions). Research limitations/implications Mental health themes were not the primary focus while research was planned and conducted. They were revealed as results of secondary qualitative data analysis. Therefore, additional mental health-focused mixed methods research is needed to verify the conclusions. The paper is written on the results of the research project “Social Housing and Homelessness” (SOHOME), implemented at the University of Luxembourg with the financial support of the Fonds National de la Recherche of

Heterozygous variants in the glucocerebrosidase GBA gene are an increasingly recognized risk factor for Parkinson's disease (PD). Due to the pseudogene GBAP1 that shares 96\% sequence homology with the GBA coding region, accurate variant calling by array-based or short-read sequencing methods remains a major challenge in understanding the genetic landscape of GBA-related PD. We established a novel long-read sequencing technology for assessing the full length of the GBA gene. We used subsequent regression models for genotype-phenotype analyses. We sequenced 752 patients with parkinsonism and 806 healthy controls of the Luxembourg Parkinson's study. All GBA variants identified showed a 100% true positive rate by Sanger validation. We found 12% of unrelated PD patients carrying GBA variants. Three novel variants of unknown significance (VUS) were identified. Using a structure-based approach, we defined a potential risk prediction method for VUS. This study describes the full landscape of GBA-related parkinsonism in Luxembourg, showing a high prevalence of GBA variants as the major genetic risk for PD. Our approach provides an important advancement for highly accurate GBA variant calling, which is essential for providing access to emerging causative therapies for GBA carriers.

BACKGROUND: As gene-targeted therapies are increasingly being developed for Parkinson's disease (PD), identifying and characterizing carriers of specific genetic pathogenic variants is imperative. Only a small fraction of the estimated number of subjects with monogenic PD worldwide are currently represented in the literature and availability of clinical data and clinical trial-ready cohorts is limited. OBJECTIVE: The objectives are to (1) establish an international cohort of affected and unaffected individuals with PD-linked variants; (2) provide harmonized and quality-controlled clinical characterization data for each included individual; and (3) further promote collaboration of researchers in the field of monogenic PD. METHODS: We conducted a worldwide, systematic online survey to collect individual-level data on individuals with PD-linked variants in SNCA, LRRK2 VPS35, PRKN, PINK1, DJ-1, as well as selected pathogenic and risk variants in GBA and corresponding demographic, clinical, and genetic data. All registered cases underwent thorough quality checks, and pathogenicity scoring of the variants and genotype-phenotype relationships were analyzed. RESULTS: We collected 3888 variant carriers for our analyses, reported by 92 centers (42 countries) worldwide. Of the included individuals 3185 had a diagnosis of PD (ie, 1306 LRRK2, 115 SNCA, 23 VPS35 429 PRKN, 75 PINK1, 13 DJ-1, and 1224 GBA) and 703 were unaffected (ie, 328 LRRK2, 32 SNCA, 3 VPS35, 1 PRKN, 1 PINK1, and 338 GBA). In total, we identified 269 different pathogenic variants; 1322 individuals in our cohort (34\%) were indicated as not previously published. CONCLUSIONS: Within the MJFF Global Genetic PD Study Group, we (1) established the largest international cohort of affected and unaffected individuals carrying PD-linked variants; (2) provide harmonized and quality-controlled clinical and genetic data for each included individual; (3) promote collaboration in the field of genetic PD with a view toward cl

A growing number of studies suggest that aging is associated with a decrease in efficacy of cognitive pain modulation. Resting state functional connectivity (rsFC) analysis of the brain offers one way of investigating the potential neural mechanisms that may underly this age-related decline. In this study, 32 young (26.7 ± 4.3 years) and 32 healthy older (68.3 ± 7.1 years) adults underwent a 6-minute resting state fMRI scan, as well as a pain distraction paradigm. In the latter, participants received painful heat stimuli while performing either an easy or a difficult working memory task. We performed region-of-interest (ROI) to ROI rsFC analysis of the imaging data, focusing on regions implicated in pain processing and descending pain control. We then examined the relationship between rsFC parameters and the magnitude of the distraction effect (the reduction in perceived pain intensity during the difficult vs the easy task). Older adults showed reduced connectivity compared to young adults between several descending pain modulatory regions, including the ACC and PAG, the right secondary somatosensory cortex (SII) and right dorsolateral prefrontal cortex and between the ACC and left amygdala. Importantly, rsFC in older adults correlated positively with the distraction effect, between several regions including the right SI and right amygdala, the left SI and right insula and between the ACC and left amygdala. Our findings thus demonstrate, for the first time, that reduced cognitive pain modulation in older age is directly associated with decreased rsFC within key nodes of the descending pain control network.

Background. While older people report acute and chronic pain more often than younger people, and, therefore, would benefit significantly from non-pharmacological pain treatment, little is known about how age affects different psychological strategies of pain modulation. The few studies on cognitive distraction from pain suggest a reduced pain relief in older adults, whereas studies on placebo analgesia revealed inconsistent results. So far, distraction and hypnotic analgesia have hardly been investigated in aging. Methods. Healthy young and older participants underwent either a cognitive pain distraction task (working memory task), a placebo analgesia realized with a sham TENS intervention, a hypnotic analgesia intervention or a verbal pain distraction intervention, while receiving non-painful and moderate painful individually adjusted transdermal electrical pulse trains to the inner forearm. Pain ratings and pain-related evoked potentials via 64-channel EEG were recorded. Results. First analyses on the currently small sample suggest a differential impact of age on pain modulation strategies. Since the current sample size is too small to draw reliable conclusions, results will be presented and discussed at the conference. Conclusion. Our results will contribute to a deeper understanding on the efficacy of cognitive pain modulation in aging, helping to optimize pain treatments in this population.

The ocean’s nitrogen is largely fixed by cyanobacteria, including Trichodesmium, which forms aggregates comprising hundreds of filaments arranged in organized architectures. Aggregates often form upon exposure to stress and have ecological and biophysical characteristics that differ from those of single filaments. Here, we report that Trichodesmium aggregates can rapidly modulate their shape, responding within minutes to changes in environmental conditions. Combining video microscopy and mathematical modeling, we discovered that this reorganization is mediated by “smart reversals” wherein gliding filaments reverse when their overlap with other filaments diminishes. By regulating smart reversals, filaments control aggregate architecture without central coordination. We propose that the modulation of gliding motility at the single-filament level is a determinant of Trichodesmium’s aggregation behavior and ultimately of its biogeochemical role in the ocean.

Affecting over 10 million people worldwide, Parkinson’s disease is the second most common neurodegenerative disorder. With only 10% of cases having a known genetic cause, PD aetiology largely remains an enigma. Endogenous factors such as genetic predisposition, and exogenous factors such as exposure to toxins and lifestyle choices, interplay in the initiation and acceleration of the disease. Despite some common hallmarks such as nigrostriatal degeneration and Lewy bodies pathology, PD clinical picture largely varies across patients. Non-motor symptoms are common and thought to emerge up to 20 years prior to diagnosis, and they range from gastro-intestinal dysfunction to sleep disturbances to hallucinations. 90% of PD patients present at least one neuropsychiatric symptom, and about 30% of total patients develop dementia. Interventions aimed to prevent or slowdown disease progression require a better understanding of the early molecular events which foster neuronal dysfunction and death. Longitudinal studies which allow the investigation of early pathological stages are challenging to achieve on patients-based study only, thus largely rely on the use of animal models. Specifically, rodents have very similar anatomy, physiology, and genetics to humans, and a good set of genetic/molecular tools are available to generate pathological models. In the present thesis, we ventured into the investigation of alpha-synuclein dependent and independent models of PD, to unravel the early molecular events driving PD pathogenesis. Firstly, we investigated a genetic mouse model overexpressing the human, E46K mutated alpha-synuclein gene. We characterised neurodegeneration in the nigrostriatal pathway and motor deficits, detecting characteristics of an early-PD phenotype. Aiming to understand the molecular events driving neurodegeneration, we profiled the ventral midbrain transcriptome at different ages, uncovering that transcriptional changes are an early response to the alpha-synucl

Bioconvection, the active self-sustaining transport phenomenon triggered by the accumulation of motile microbes under competing physico-chemical cues, has been long studied, with recent reports suggesting its role in driving ecologically-relevant fluid flows. Yet, how this collective behaviour impacts the ecophysiology of swimming microbes remains unexplored. Here, through physicochemical profiles and physiological characterizations analysis of the permanently stratified meromictic Lake Cadagno, we characterize the community structure of a dense layer of anaerobic phototrophic sulfur bacteria, and report that the associated physico-chemical conditions engender bioconvection when bulk of the motile purple sulfur bacterium Chromatium okenii synchronize their movement against the gravity direction. The combination of flow cytometry and fluorescent in situ hybridization (FISH) techniques uncover the eco-physiological effects resulting from bioconvection, and simultaneous measurements using dialysis bags and 14C radioisotope, allowed us to quantify in situ the diurnal and nocturnal CO2 fixation activity of the three co-existing species in the bacterial layer. The results provide a direct measure of the cellular fitness, with comparative transcriptomics data - of C. okenii populations present in regions of bioconvection vis-a-vis populations in bioconvection-free regions - indicating the transcripts potentially involved in the bioconvection process. This work provides direct evidence of the impact of bioconvection on C. okenii metabolism, and highlights the functional role of bioconvection in enhancing the metabolic advantage of C. okenii relative to other microbial species inhabiting the microbial layer.

Pathogenic copy number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts.Here, we introduce the CNV-ClinViewer, an open-source web-application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators patient care and for basic scientists translational genomic research.The web-application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.Supplementary data are available at Bioinformatics online.

This work examines the practice of reading aloud in the interactional context of adult participants engaging in an interface-mediated collaborative game activity. With a conversation analytic approach onto video data of user studies, empirical cases of reading aloud are presented. It is shown how participants multimodally co-organise reading aloud in-interaction for providing accessibility to game text in a game that is unfamiliar to them. With reading aloud, participants meet the interactional challenge of making game text audibly accessible that is not always visually accessible for all participant alike. This practice is not only conducted for another but with another in a truly joint fashion, working as a continuer to accomplish the unfamiliar game.

As space activities continue to develop and increase in number, so do environmental concerns in outer space. For decades now, humanity has continuously sent satellites into Earth orbits without caring for potential environmental consequences in outer space. Ultimately, these actions have proven to raise issues regarding the sustainability of the activity; issues which are now being addressed legally. Satellites were the first venture of humanity into space, and it is fair to admit we did not know better at the time. We do now. With the development of new types of space missions, such as space resources-related activities, it is safe to assume that new serious environmental problems will arise as well. Based on previous experience both on Earth and in outer space, it is logical, but also imperative, to question the environmental impact of these space resources activities and to consider legal solutions to promote and facilitate their sustainability. Accordingly, this research assesses the applicability of existing rules and mechanisms promoting environmental protection and sustainability in outer space to the case of the exploitation of space resources. To that end, an array of mechanisms is considered such as the framework of the UN Space Treaties, international environmental law, non-legally binding instruments, such as the space debris mitigation guidelines and COSPAR’s planetary protection policy, as well as national space legislations. Ultimately, this work aims at drafting the roadmap for the environmentally sustainable exploitation of space resources from a legal standpoint. It recommends the adoption of a mix of interdisciplinary approaches which balances a national effective approach with international guiding rules.

The European Union (EU) and its member states are the world’s largest development donor, but the European financial architecture for development suffers from well-documented problems of fragmentation. EU member states’ decision to convene the Wieser Group in April 2019 raised expectations over rationalising the roles of the European Investment Bank (EIB) and the European Bank for Reconstruction and Development (EBRD). However, the Council of the EU showed little enthusiasm for the group’s call to create a single entity for external development finance. Twelve months later, member states endorsed Team Europe, an alternative approach which mobilises the resources of the EIB, the EBRD, the European Commission and national development finance institutions in support of shared development goals. This article seeks to explain why the Council ultimately preferred Team Europe’s coordinated approach to the Wieser Report’s centralised vision of a European Climate and Sustainable Development Bank. In keeping with new intergovernmentalism, we find that member states’ willingness to cooperate but reluctance to delegate, and the aim of EU institutions to protect their turf, favoured Team Europe. We see few reasons to expect radical changes in this domain despite continued doubts over the effectiveness and coherence of European development finance.

BACKGROUND: Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. RESULTS: We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19-positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19-positive individuals compared to healthy controls. CONCLUSIONS: Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients. Video Abstract.

In the fight for individual privacy against online surveillance and personal data breaches, blockchain developers often pitch encrypted wallets as solutions. Five examples from 2021 and 2022 involve Big Tech companies or large European governments. On the private side, Jack Dorsey’s Block company announced the Web5 Self-Sovereign Identity (SSI) Service. Meta and Twitter added support for fictional identities – tokenised avatars or profile pictures like Bored Apes and CryptoPunks, registered to Web3 wallets that putatively offer “self-sovereign ownership”. On the public side, the European Commission funded SSI wallet trials for digital diploma credentials. Germany’s federal government launched a mobile driving licence (mDL), stored in a SSI wallet. This one term, “SSI”, is associated with varying sets of technologies and ethical principles. Following complaints that “SSI” generates confusion, I offer a typology that highlights four semantic contradictions as well as a concept map to guide future research.

Le courant « droit et littérature » n’est jamais défini qu’à travers le prisme de déclinaisons particulières qui ne rendent pas compte du lien originel qui unit ces deux discours. Au contraire, ces déclinaisons étouffent ce lien et lui jettent une ombre empêchant de le mettre au jour. Notre recherche vise à combler cette absence de définition originelle. Elle propose une définition générique du lien sous le terme de « présence ina$ive » afin de résoudre ce problème.

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Since Bitcoin, the blockchain space considerably evolved. One crucial piece of software to interact with blockchains and hold private-public key pairs to distinct crypto-assets and securities are wallets. Wallet software can be offered by liable third-parties (‘custodians’) who hold certain rights over assets and transactions. As parties subject to financial regulation, they are to uphold Anti-money Laundering and Combating the Financing of Terrorist (AML/CFT) standards by undertaking Know-Your-Customer (KYC) checks on users of their services. In juxtaposition, wallet software can also be issued without the involvement of a liable third-party. As no KYC is performed and users have full ‘freedom to act’, such ‘non-custodial’ wallet software is popular in criminal undertakings. They are required to interact with peer-to-peer applications and organisations running on blockchains whose benefits are not the subject of this paper. To date, financial regulation fails to adequately address such wallet software because it presumes the existence of a registered, liable entity offering said software. As illustrated in the case of Tornado Cash, financial regulation fails to trace chains of secondary liability. Alas, the considered solution is a systematic surveillance of all transactions. Against this backdrop, this paper sets forth an alternative approach rooted in copyright law. Concepts that pertain to secondary liability prove of value to develop a flexible, principles-based approach to the regulation of non-custodial wallet software that accounts for both, infringing and non-infringing uses.

Background Parkinson's disease (PD) is the fastest growing neurodegenerative disorder, with affected individuals expected to double during the next 20 years. This raises the urgent need to better understand the genetic architecture and downstream cellular alterations underlying PD pathogenesis, in order to identify more focused therapeutic targets. While only ~10\% of PD cases can be clearly attributed to monogenic causes, there is mounting evidence that additional genetic factors could play a role in idiopathic PD (iPD). In particular, common variants with low to moderate effect size in multiple genes regulating key neuroprotective activities may act as risk factors for PD. In light of the well-established involvement of mitochondrial dysfunction in PD, we hypothesized that a fraction of iPD cases may harbour a pathogenic combination of common variants in nuclear-encoded mitochondrial genes, ultimately resulting in neurodegeneration.Methods: To capture this mitochondria-related 'missing heritability', we leveraged on existing data from previous genome-wide association studies (GWAS) i.e., the large PD GWAS from Nalls and colleagues. We then used computational approaches based on mitochondria-specific polygenic risk scores (mitoPRSs) for imputing the genotype data obtained from different iPD case-control datasets worldwide, including the Luxembourg Parkinson\textquoterights Study (412 iPD patients and 576 healthy controls) and the COURAGE-PD cohorts (7270 iPD cases and 6819 healthy controls).Results: Applying this approach to gene sets controlling mitochondrial pathways potentially relevant for neurodegeneration in PD, we demonstrated that common variants in genes regulating Oxidative Phosphorylation (OXPHOS-PRS) were significantly associated with a higher PD risk both in the Luxembourg Parkinson\textquoterights Study (odds ratio, OR=1.31[1.14-1.50], p=5.4e-04) and in COURAGE-PD (OR=1.23[1.18-1.27], p=1.5e-29). Functional analyses in primary skin fibroblasts and in

Older people, suffering from pain and its consequences more often than younger people, would benefit significantly from non-pharmacological pain treatment. So far, little is known about how age affects psychological pain modulation strategies. Preliminary findings hint towards a less efficient pain inhibition through cognition-based pain modulation strategies, as cognitive distraction from pain. Here, executive functions (EFs) have been considered a key factor in the age – pain relationship, with age-related cognitive decline in EFs being associated with reduced pain relief through distraction in older adults. We investigated influence of four core EFs on distraction from pain in aging. In a two-session design, healthy young (18-30 years) and older participants (60+ years) performed a Go-Nogo task, the Stroop-Color-Word-Task, the Sternberg-Task, and the Attentional Network Task. Afterwards, participants performed a pain distraction task, namely a n-Back working memory task with low and high cognitive load, during which participants received individually adjusted transdermal electrical pulse trains in non-painful and moderately painful intensities to the inner forearm. Ratings of intensity and unpleasantness were collected and stimulus-related (EF tasks) and pain-related evoked potentials were recorded with a 64-channel EEG. Unexpectedly, first analyses on the currently small sample suggest a more efficient pain relief through distraction under low relative to high cognitive load in older adults. The distraction effect was related to EFs, some of which showed age-related cognitive impairment. Our findings could lead to a better understanding how to adapt pain treatments in this population by including selective cognitive trainings and optimizing distraction task difficulty.

Current computational models of cognitive control exhibit notable limitations. In machine learning, artificial agents are now capable of performing complex tasks but often ignore critical constraints such as resource limitations and how long it takes for the agent to make decisions and act. Conversely, cognitive control models in psychology are limited in their ability to tackle complex tasks (e.g., play video games) or generalize across a battery of simple cognitive tests. Here we introduce CogPonder, a flexible, differentiable, cognitive control framework that is inspired by the Test-Operate-Test-Exit (TOTE) architecture in psychology and the PonderNet framework in machine learning. CogPonder functionally decouples the act of control from the controlled processes by introducing a controller that acts as a wrapper around any end-to-end deep learning model and decides when to terminate processing and output a response, thus producing both a response and response time. Our experiments show that CogPonder effectively learns from data to generate behavior that closely resembles human responses and response times in two classic cognitive tasks. This work demonstrates the value of this new computational framework and offers promising new research prospects for both psychological and computer sciences.

The Warlux project aims to reconstruct life stories during the Second World War, both at the front and among the relatives of forced recruits in Luxembourg. The research project will come to an end this summer. Yet science is actually only scratching the surface.

Invited talk for the Environmental Chemistry and Biogeochemistry Seminar at Umeå University, 17 March 2023, Virtual Event. Many thanks to Andriy Rebryk for the invitation!

In industrial extrusion processes, increasing shear rates can lead to higher production rates. However, at high shear rates, extruded polymers and polymer compounds often exhibit melt instabilities ranging from stick-slip to sharkskin to gross melt fracture. These instabilities result in challenges to meet the specifications on the extrudate shape. Starting with an existing published data set on melt instabilities in polymer extrusion, we assess the suitability of clustering, unsupervised machine learning algorithms combined with feature selection, to extract and identify hidden and important features from this data set, and their possible relationship with melt instabilities. The data set consists of both intrinsic features of the polymer as well as extrinsic features controlled and measured during an extrusion experiment. Using a range of commonly available clustering algorithms, it is demonstrated that the features related to only the intrinsic properties of the data set can be reliably divided into two clusters, and that in turn, these two clusters may be associated with either the stick-slip or sharkskin instability. Furthermore, using a feature ranking on both the intrinsic and extrinsic features of the data set, it is shown that the intrinsic properties of molecular weight and polydispersity are the strongest indicators of clustering.

The overarching theme of this PhD thesis is human mobility and its externalities, particularly in the context of labour and health economics. Through rigorous modelling and analysis, the three chapters of the thesis demonstrate the potential benefits of policies that regulate human mobility. In the first chapter of my PhD, I examine how language training can improve the functioning of the labour market, with a particular focus on immigrants with high skills who face language barriers. I argue that fully funding the cost of language acquisition for migrants can bring significant benefits to the economy and migrants, but may marginally worsen the labour market performance of low-skilled natives. Using a search and matching framework with two-dimensional skill heterogeneity, I model the effects of a language acquisition subsidy on migrants' labour market integration and its impact on natives' labour market performance. My study finds that subsidizing language acquisition costs may increase the GDP of the German economy by approximately ten billion dollars by decreasing the aggregate unemployment rate and skill mismatch rate and increasing the share of job vacancies requiring high generic skills. The second chapter of my PhD explores the challenges involved in devising social contact limitation policies as a means of controlling infectious disease transmission. Using an economic-epidemiological model of COVID-19 transmission, I evaluate the effectiveness of different intervention strategies and their consequences on public health, social welfare and economic outcomes. The findings emphasize the importance of responsiveness in implementing social contact limitations, rather than solely focusing on their stringency, and suggest that early interventions lead to the lowest losses in economy and mental well-being for a given number of life losses. The study has broader implications for managing the societal impact of infectious diseases and highlights the need to continue re

Ethereum's public distributed ledger can issue tokenised voting rights that are tradable on crypto-asset exchanges by potentially anyone. Ethereum thus enables global, unincorporated associations to conduct governance experiments. Such experiments are crucial to Decentralised Finance (DeFi). DeFi is a nascent field of unlicensed, unregulated, and non-custodial financial services that utilise public distributed ledgers and crypto-assets rather than corporate structures and sovereign currencies. The inaugural Bloomberg Galaxy DeFi Index, launched in August 2021, included nine Ethereum-based projects – non-custodial exchanges as well as lending and derivatives platforms. Each project is governed, at least in part, by unregistered holders of tokenised voting rights (also known as governance tokens). Token-holders typically vote for or against coders' improvement proposals that pertain to anything from the allocation of treasury funds to a collateral's risk parameters. DeFi's governance thus depends on the distribution and exercise of tokenised voting rights. Since archetypal DeFi projects are not managed by companies or public institutions, not much is known about DeFi's governance. Regulators and law-makers from the United States recently asked if DeFi's governance entails a new class of “shadowy” elites. In response, we conducted an exploratory, multiple-case study that focused on the tokenised voting rights issued by the nine projects from Bloomberg's inaugural Galaxy DeFi index. Our mixed methods approach drew on Ethereum-based data about the distribution, trading, staking, and delegation of voting rights tokens, as well as project documentation and archival records. We discovered that DeFi projects' voting rights are highly concentrated, and the exercise of these rights is very low. Our theoretical contribution is a philosophical intervention: minority rule, not “democracy”, is the probable outcome of token-tradable voting rights and a lack of applicable anti-conce

Machine Learning (ML) has become indispensable for real-world complex systems, such as perception systems of autonomous systems and vehicles. However, ML-based systems are sensitive to input data, faults, and malicious threats that can degrade output quality and compromise the complete system's correctness. Ensuring a reliable output of ML-based components is crucial, especially for safety-critical systems. In this paper, we investigate architectures of perception systems using N-version programming for ML to mitigate the dependence on a singular ML component and combine it with a time-based rejuvenation mechanism to maintain a healthy system over extended periods. We propose models and functions to evaluate the reliability of N-version perception systems subject to faults, malicious threats, and rejuvenation. Our numerical experiments show that a rejuvenation mechanism could benefit a multiple-version system, with a reliability improvement superior to 13%. Also, the results indicate that rejuvenation could improve output reliability when ML modules' accuracy is high.

Space systems security is an emerging discipline in cyberphysical systems security domain. The research conducted in the field has to be done using realistic assumptions and pieces of equipment that take into account multi-disciplinary character of space systems. In CritiX, we've built the Space Systems Safety and Security lab to facilitate the research on space systems and to support the education of future generation of space systems security specialists.

With growing adoption of Distributed Ledger Technologies, their networks must scale while maintaining efficient communication for the underlying consensus and replication mechanisms. New content distribution concepts like Named Data Networking create opportunities to achieve this goal. We present and evaluate XRP-NDN overlay, a solution to increase communication efficiency for consensus-validation blockchains like XRP Ledger. We send consensus messages over different communication models and show that the chosen model lowers the number of messages at node level to minimum, while maintaining or improving performance by leveraging overlay advantages.

Mobile devices are pervasively used for a variety of tasks, including the processing of sensitive data in mobile apps. While in most cases access to this data is legitimate, malware often targets sensitive data and even benign apps collect more data than necessary for their task. Therefore, researchers have proposed several frameworks to detect and track the use of sensitive data in apps, so as to disclose and prevent unauthorized access and data leakage. Unfortunately, a review of the literature reveals a lack of consensus on what sensitive data is in the context of technical frameworks like Android. Authors either provide an intuitive definition or an ad-hoc definition, derive their definition from the Android permission model, or rely on previous research papers which do or do not give a definition of sensitive data. In this paper, we provide an overview of existing definitions of sensitive data in literature and legal frameworks. We further provide a sound definition of sensitive data derived from the definition of personal data of several legal frameworks. To help the scientific community further advance in this field, we publicly provide a list of sensitive sources from the Android framework, thus starting a community project leading to a complete list of sensitive API methods across different frameworks and programming languages.

Graph related tasks, such as graph classification and clustering, have been substantially improved with the advent of graph neural networks (GNNs). However, existing graph embedding models focus on homogeneous graphs that ignore the heterogeneity of the graphs. Therefore, using homogeneous graph embedding models on heterogeneous graphs discards the rich semantics of graphs and achieves average performance, especially by utilizing unlabeled information. However, limited work has been done on whole heterogeneous graph embedding as a supervised task. In light of this, we investigate unsupervised distributed representations learning on heterogeneous graphs and propose a novel model named G-HIN2Vec, Graph-Level Heterogeneous Information Network to Vector. Inspired by recent advances of unsupervised learning in natural language processing, G-HIN2Vec utilizes negative sampling technique as an unlabeled approach and learns graph embedding matrix from different predefined meta-paths. We conduct a variety of experiments on three main graph downstream applications on different socio-demographic cardholder features, graph regression, graph clustering, and graph classification, such as gender classification, age, and income prediction, which shows superior performance of our proposed GNN model on real-world financial credit card data.