The mod 2 cohomology rings of congruence subgroups in the Bianchi groups

E-print/Working paper (in press)

We provide new tools for the calculation of the torsion in the cohomology of congruence subgroups in the Bianchi groups : An algorithm for finding particularly useful fundamental domains, and an analysis ... [more ▼]

We provide new tools for the calculation of the torsion in the cohomology of congruence subgroups in the Bianchi groups : An algorithm for finding particularly useful fundamental domains, and an analysis of the equivariant spectral sequence combined with torsion subcomplex reduction. [less ▲]

Teacher-Student Relationships and Student Outcomes: A Systematic Review of Meta-Analyses and Second-Order Meta-Analysis

E-print/Working paper (2023)

Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations ... [more ▼]

Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations between TSRs and, for example, academic achievement, a lack of disruptive behavior, school engagement, peer relationships, motivation, executive functions, and general well-being. However, these meta-analyses have differed substantially in TSR-outcome relationships, moderators, and quality, thus complicating the interpretation of these findings. In this preregistered systematic review of meta-analyses plus original second-order meta-analyses (SOMAs), we aimed to (a) synthesize the meta-analytic evidence on relationships between TSRs and student outcomes, (b) map influential moderators of these relationships, and (c) assess the methodological quality of the meta-analyses. We synthesized over 70 years of educational research in 24 meta-analyses encompassing a total of 116 effect sizes based on more than 2 million prekindergarten and K-12 students. We conducted several three-level SOMAs and found that TSRs had similar strong significant relationships with eight clusters of outcomes: academic achievement, academic emotions, appropriate student behavior, behavior problems, executive functions and self-control, motivation, school belonging and engagement, and student well-being. Age, gender, and informant (student-, peer-, or teacher-assessments) were the most frequently examined moderators in prior research, and our moderator analyses suggested student grade level and social minority status as moderators. We further found large differences in quality between the meta-analyses, and these differences were not associated with the TSR-outcome relationships. These results map the field of TSR research; present their relationships, moderators, and meta-analytic quality; and show how TSRs can contribute to improving outcomes in students via relationship building. Future research should follow meta-analytic open science procedures to improve quality and reproducibility. [less ▲]

Investigating Preservice Teachers’ Attitudes Toward Lesbian, Gay, and Bisexual Students in Luxembourg

E-print/Working paper (2023)

Lesbian, gay, and bisexual (LGB) students face victimization in multiple contexts, including the educational context. Here, teachers can serve as an important resource for LGB students. However, teachers ... [more ▼]

Lesbian, gay, and bisexual (LGB) students face victimization in multiple contexts, including the educational context. Here, teachers can serve as an important resource for LGB students. However, teachers who are prejudiced against students from sexual minorities might not be able to fulfill this role. Accordingly, it is important to find out more about teachers' attitudes and their correlates, as such information can provide starting points for sensitization interventions in teacher education programs, which have the potential to improve the situation of LGB students in the school setting. In the present preregistered questionnaire study, we investigated the attitudes of 138 preservice teachers from the University of Luxembourg toward LGB students and tried to identify predictors of teachers’ attitudes. Results suggested that Luxembourgish preservice teachers hold mostly positive attitudes toward LGB students. Using correlation and multiple regression analyses, we identified the frequency of participants’ contact with LGB people in family or friend networks, hypergendering tendencies, sexual orientation, and religiosity as reliable predictors of attitudes toward LGB students. Age, gender, and right-wing conservatism did not reliably predict preservice teachers’ attitudes in the regression models. Our findings thus offer support for intergroup contact theory and have implications for teacher education in Luxembourg. [less ▲]

Reconfigurable Intelligent Surfaces Enhanced NOMA D2D Communications Underlaying UAV Networks

E-print/Working paper (2023)

Device-to-device (D2D) communications offers high spectral efficiency, low energy consumption and transmission latency. However, one of the main limitations of D2D communications is co-channel ... [more ▼]

Device-to-device (D2D) communications offers high spectral efficiency, low energy consumption and transmission latency. However, one of the main limitations of D2D communications is co-channel interference from underlaying wireless system. Reconfigurable intelligent surfaces (RIS) is a promising technology because it can manipulate the electromagnetic waves in their environment to overcome interference and enhance wireless communications. This paper considers RIS enhanced D2D communications underlaying unmanned aerial vehicle (UAV) networks with non-orthogonal multiple access (NOMA). The objective is to maximize the sum rate of NOMA D2D communications by optimizing the power budget of D2D transmitter, NOMA power allocation coefficients of D2D receivers and passive beamforming of RIS while guaranteeing the quality of services of UAV user. Due to non-convexity, the optimization problem is intractable and challenging to handle. Therefore, it is solved in two parts using alternating optimization. Simulation results unviel the performance of the proposed RIS enhanced D2D communications scheme. Results demonstrate that the proposed scheme ach [less ▲]

NOMA-Based Backscatter Communications: Fundamentals, Applications, and Advancements

E-print/Working paper (2023)

Developing wireless communication technologies is an ongoing process to satisfy the requirements of new applications and the increasing proliferation of interconnected devices. Using non-orthogonal ... [more ▼]

Developing wireless communication technologies is an ongoing process to satisfy the requirements of new applications and the increasing proliferation of interconnected devices. Using non-orthogonal multiple access (NOMA) and backscatter communication (BC) has surfaced as an advantageous approach for enhancing energy efficiency (EE), maximizing sum rates, ensuring security, and optimizing resource allocation. NOMA permits multiple users to share time and frequency resources even without the requirement of antenna arrays, whereas BC employs ambient RF signals for low-power communication. By integrating the advantages of NOMA and BC, NOMA-based BC provides a solution for future energy-efficient and low-power networks. Despite its potential, there is a lack of a comprehensive overview of NOMA-BC, necessitating a systematic survey that covers its principles, applications, challenges, and future directions. This survey aims to bridge the gap by exploring NOMA-BC within B5G and 6G networks. We delve into its technical aspects, performance optimization techniques, and real-world applications to enhance understanding and knowledge. First, we cover topics such as enhancing EE, maximizing the sum rates, ensuring security, and optimizing resource allocation. Our primary goal is to provide researchers and practitioners with valuable insights that enable them to grasp the capabilities and benefits of NOMA-BC. To achieve this, we comprehensively analyze various schemes' performance by presenting detailed summary tables. These analyses cover a range of scenarios, methods, and objectives, focusing on emerging B5G technologies such as reconfigurable intelligent surfaces (RIS), visible light communication (VLC), and unmanned aerial vehicle (UAV) communication. By examining NOMA-BC's effectiveness within these contexts, we aim to provide a holistic view of its potential and applicability in diverse technological domains. Moreover, our survey identifies and discusses open research challenges and proposes future directions to guide researchers toward unexplored areas and facilitate advancements in NOMA-BC. [less ▲]

RIS-Assisted Energy-Efficient LEO Satellite Communications with NOMA

E-print/Working paper (2023)

This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the ... [more ▼]

This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the LEO satellite and the passive beamforming of RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the energy efficiency maximization problem is non-convex. In practice, obtaining the optimal solution for such problems is very challenging. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate satellite transmit power towards each ground terminal using the Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. We also compare our solution with a benchmark framework having a fixed phase shift design and a conventional NOMA framework without involving RIS. Numerical results show that the proposed optimization framework achieves 21.47% and 54.9% higher energy efficiency compared to the benchmark and conventional frameworks. [less ▲]

Motile bacteria leverage bioconvection for eco-physiological benefits in a natural aquatic environment

E-print/Working paper (2023)

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 ... [more ▼]

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. [less ▲]

OPTWIN: Drift identification with optimal sub-windows

E-print/Working paper (2023)

Online Learning (OL) is a field of research that is increasingly gaining attention both in academia and industry. One of the main challenges of OL is the inherent presence of concept drifts, which are ... [more ▼]

Online Learning (OL) is a field of research that is increasingly gaining attention both in academia and industry. One of the main challenges of OL is the inherent presence of concept drifts, which are commonly defined as unforeseeable changes in the statistical properties of an incoming data stream over time. The detection of concept drifts typically involves analyzing the error rates produced by an underlying OL algorithm in order to identify if a concept drift occurred or not, such that the OL algorithm can adapt accordingly. Current concept-drift detectors perform very well, i.e., with low false negative rates, but they still tend to exhibit high false positive rates in the concept-drift detection. This may impact the performance of the learner and result in an undue amount of computational resources spent on retraining a model that actually still performs within its expected range. In this paper, we propose OPTWIN, our “OPTimal WINdow” concept drift detector. OPTWIN uses a sliding window of events over an incoming data stream to track the errors of an OL algorithm. The novelty of OPTWIN is to consider both the means and the variances of the error rates produced by a learner in order to split the sliding window into two provably optimal subwindows, such that the split occurs at the earliest event at which a statistically significant difference according to either the 𝑡- or the 𝑓 -tests occurred. We assessed OPTWIN over the MOA framework, using ADWIN, DDM, EDDM, STEPD and ECDD as baselines over 7 synthetic and real-world datasets, and in the presence of both sudden and gradual concept drifts. In our experiments, we show that OPTWIN surpasses the F1-score of the baselines in a statistically significant manner while maintaining a lower detection delay and saving up to 21% of time spent on retraining the models. [less ▲]

Temperature and Joint Time Use

E-print/Working paper (2023)

We combine exogenous variation in temperature at the county-day level in the U.S. with daily time use data to examine the effect of temperature on joint time use. We show that low temperatures reduce time ... [more ▼]

We combine exogenous variation in temperature at the county-day level in the U.S. with daily time use data to examine the effect of temperature on joint time use. We show that low temperatures reduce time spent with friends but increase time spent with family. Conversely, high temperatures increase time alone but reduce time with family. We also provide evidence of the effect of temperature on joint time use being location-dependent. We rationalize this finding using a model in which the chosen time allocation is the outcome of a dual-self decision process with an indoor and an outdoor self. The two selves have different tastes for time alone, time with family, and time with friends. Weather conditions can change the influence of each self, and thereby the corresponding preferences for joint time use. We test the predictions of the model empirically by drawing on methods from the household economics literature. The test results support the hypothesis that weather affects joint time use insofar it affects where the activities take place. [less ▲]

Measured foliations at infinity and constant mean curvature surfaces in quasi-Fuchsian manifolds close to the Fuchsian locus

E-print/Working paper (2023)

Recherche en histoire : les opportunités et défis du numérique

E-print/Working paper (2023)

Transferability of European-derived cardiometabolic polygenic risk scores in the South Asians and their interplay with family history 2023.03.20.23287470

E-print/Working paper (2023)

Background & Aims We aimed to investigate the effect of polygenic risk scores (PRSs) derived from individuals of European (EUR) ancestry on common diseases among individuals of South Asian (SAS) ancestry ... [more ▼]

Background & Aims We aimed to investigate the effect of polygenic risk scores (PRSs) derived from individuals of European (EUR) ancestry on common diseases among individuals of South Asian (SAS) ancestry in the UK Biobank (UKB). Additionally, we studied the interaction between PRS and family history (FH) in the same population.Methods To calculate the PRS, we used a previously published panel of SNPs derived from the EUR population and applied it to the individuals of SAS ancestry from the UKB study. We applied the PRS using summary statistics from genome-wide association studies (GWAS) for cardiometabolic and lifestyle diseases such as coronary artery disease (CAD), obesity, and type 2 diabetes (T2D). Each PRS was adjusted according to an individual\textquoterights predicted genetic ancestry to derive an adjusted PRS (aPRS). We calculated the percentiles based on aPRS and divided them according to the percentiles into three categories: low, intermediate, and high. Considering the intermediate-aPRS percentile as a reference, we compared the low and high aPRS categories and generated the odds ratio (OR) estimates.Results The risk of developing severe obesity for individuals of SAS ancestry was almost threefold higher for individuals with high aPRS than for those with intermediate aPRS, with an OR of 3.67 (95% CI = 2.47-5.48, P < 0.01). While the risk of severe obesity was lower in the low-aPRS group (OR = 0.19, CI = 0.05\textendash0.52, P < 0.01). Comparable results were found in the EUR data, where the low-PRS group had an OR of 0.26 (95% CI= 0.24-0.3, P < 0.01) and the high-PRS group had an OR of 3.2 (95% CI = 3.1-3.3, P < 0.01). We observed similar results for CAD and T2D. Further, we show that SAS individuals with a familial history of CAD and T2D with high-aPRS exhibit further higher risk to these diseases, thereby implying a greater genetic predisposition to these conditions.Conclusion Our findings suggest that using CAD, obesity, and T2D GWAS summary statistics predominantly from the EUR population have sufficient power to identify SAS individuals with higher genetic risk. With future GWAS recruiting more SAS participants and tailoring the PRSs towards SAS ancestry, we believe that the predictive power of PRS would improve. [less ▲]

Energy-Efficient RIS-Enabled NOMA Communication for 6G LEO Satellite Networks

E-print/Working paper (2023)

Reconfigurable Intelligent surfaces (RIS) have the potential to significantly improve the performance of future 6G LEO satellite networks. In particular, RIS can improve the signal quality of ground ... [more ▼]

Reconfigurable Intelligent surfaces (RIS) have the potential to significantly improve the performance of future 6G LEO satellite networks. In particular, RIS can improve the signal quality of ground terminal, reduce power consumption of satellite and increase spectral efficiency of overall network. This paper proposes an energy-efficient RIS-enabled NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals at LEO satellite and passive beamforming at RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the problem of energy efficiency maximization is formulated as non-convex. In practice, it is very challenging to obtain the optimal solution for such problems. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate efficient power for ground terminals at satellite using Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. To validate the proposed solution, numerical results are also provided to demonstrate the benefits of the proposed optimization framework. [less ▲]

The Next Generation EU (NGEU) as a catalyst for the promotion of the international role of the euro

E-print/Working paper (2023)

Recent developments in the global arena such as the COVID-19 pandemic and stresses in energy markets, made it clear that it is critical for the EU to ensure its strategic autonomy in the macroeconomic ... [more ▼]

Recent developments in the global arena such as the COVID-19 pandemic and stresses in energy markets, made it clear that it is critical for the EU to ensure its strategic autonomy in the macroeconomic field. Strengthening the international role of the euro is one of the key elements in this regard. Through timely analysis of the changes stemming from the establishment of the Next Generation EU (NGEU), we seek to understand to what extent the NGEU can serve as a catalyst for the promotion of the international role of the euro. While it is implausible that the euro will overcome the primacy of the US dollar, we center our analysis around the transformation of the EU’s presence in capital markets. Following massive issuances of green bonds under the NGEU, the EU became the largest issuer of green bonds and has the potential to progress from a small supranational issuer to a sovereign size issuer. This means that the pool of highly rated euro-denominated safe assets will expand significantly. That is where we focus our analysis and where we see the opportunity of the NGEU for unleashing the potential of the euro and boosting its international role. [less ▲]

MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations

E-print/Working paper (2023)

In many cutting-edge applications, high-fidelity computational models prove too slow to be practical and are thus replaced by much faster surrogate models. Recently, deep learning techniques have become ... [more ▼]

In many cutting-edge applications, high-fidelity computational models prove too slow to be practical and are thus replaced by much faster surrogate models. Recently, deep learning techniques have become increasingly important in accelerating such predictions. However, they tend to falter when faced with larger and more complex problems. Therefore, this work introduces MAgNET: Multi-channel Aggregation Network, a novel geometric deep learning framework designed to operate on large-dimensional data of arbitrary structure (graph data). MAgNET is built upon the MAg (Multichannel Aggregation) operation, which generalizes the concept of multi-channel local operations in convolutional neural networks to arbitrary non-grid inputs. The MAg layers are interleaved with the proposed novel graph pooling/unpooling operations to form a graph U-Net architecture that is robust and can handle arbitrary complex meshes, efficiently performing supervised learning on large- dimensional graph-structured data. We demonstrate the predictive capabilities of MAgNET for several non-linear finite element simulations and provide open-source datasets and codes to facilitate future research. [less ▲]

Pricing Dynamics and Herding Behavior of NFTs

E-print/Working paper (2023)

Non-fungible tokens (NFTs) took the digital art space by storm in 2021, generating massive amounts of volume and attracting a large number of users to a previously obscure part of blockchain technology ... [more ▼]

Non-fungible tokens (NFTs) took the digital art space by storm in 2021, generating massive amounts of volume and attracting a large number of users to a previously obscure part of blockchain technology. Still, very little is known about the determinants that contribute to NFT pricing and the market dynamics. This paper attempts to evaluate these factors analyzing 860,067 art NFTs that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales. We introduce a first-of-its-kind ranking system for NFT artists, adding a novel dimension to our analysis. Our results suggest that market liquidity and intrinsic value strongly predict average price of NFTs. Contrarily, social media activity surprisingly shows a negative association with NFT prices. We also uncover the dominance of a small group of artists, demonstrating the pronounced 'superstar effect' and herding behavior within the NFT market. This market dynamic, however, shows signs of shifting towards independent decision-making during extreme market volatility. [less ▲]

Planktonic Active Matter

E-print/Working paper (2023)

Planktonic active matter represents an emergent system spanning different scales: individual, population and community; and complexity arising from sub-cellular and cellular to collective and ecosystem ... [more ▼]

Planktonic active matter represents an emergent system spanning different scales: individual, population and community; and complexity arising from sub-cellular and cellular to collective and ecosystem scale dynamics. This cross-scale active matter system responds to a range of abiotic (temperature, fluid flow and light conditions) and biotic factors (nutrients, pH, secondary metabolites) characteristic to the relevant ecosystems they are part of. Active modulation of cell phenotypes, including morphology, motility, and intracellular organization enable planktonic microbes to dynamically interact with other individuals and species; and adapt - often rapidly - to the changes in their environment. In this chapter, I discuss both traditional and contemporary approaches to study the dynamics of this multi-scale active matter system from a mechanistic standpoint, with specific references to their local settings and their ability to actively tune the behaviour and physiology, and the emergent structures and functions they elicit under natural ecological constraints as well as due to the shifting climatic trends. [less ▲]

Self-Supervised Learning for Place Representation Generalization across Appearance Changes

E-print/Working paper (2023)

Cardiovascular risk prediction - a systems medicine approach

E-print/Working paper (2023)

Background Guidelines for the prevention of cardiovascular disease (CVD) have recommended the assessment of the total CVD risk by risk scores. Current risk algorithms are low in sensitivity and ... [more ▼]

Background Guidelines for the prevention of cardiovascular disease (CVD) have recommended the assessment of the total CVD risk by risk scores. Current risk algorithms are low in sensitivity and specificity and they have not incorporated emerging risk markers for CVD. We suggest that CVD risk assessment can be still improved. We have developed a long-term risk prediction model of cardiovascular mortality in patients with stable coronary artery disease (CAD) based on newly available machine learning and on an extended dataset of new biomarkers.Methods 2953 participants of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study were included. 184 laboratory and 21 demographic markers were ranked according to their contribution to risk of cardiovascular (CV) mortality using different data mining approaches. A self-learning bioinformatics workflow, including seven different machine learning algorithms, was developed for CV risk prediction. The study population was stratified into patients with and without significant CAD. Thereby, significant CAD was defined as a lumen narrowing of 50 or more in at least one of the coronary segments or a history of definite myocardial infarction. The machine learning models in both subpopulations were compared with established CV risk assessment tools.Results After a follow-up of 10 years, 603 (20.4%) patients died of cardiovascular causes. 95% patients without CAD deceased within ten years and 247 (13.2 %) patients with CAD within 5 years. Overall and in patients without CAD, NT-proBNP (N-terminal pro B-type natriuretic peptide), TnT (Troponin T), estimated cystatin c based GFR (glomerular filtration rate) and age were the highest ranked predictors, while in patients with CAD, NT-proBNP, GFR, CT-proAVP (C-terminal pro arginine vasopressin) and TNT were highest predictive. In the comparison with the FRS, PROCAM and ESC risk scores, the machine learning workflow produced more accurate and robust CV mortality prediction in patients without CAD. Equivalent CV risk prediction was obtained in the CAD subpopulation in comparison with the Marschner risk score. Overall, the existing algorithms in general tend to assign more patients into the medium risk groups, while the machine learning algorithms tend to have a clearer risk/no risk assignment. The framework is available upon request.Conclusion We have developed a fully automated and self-validating computational framework of machine learning techniques using an extensive database of clinical, routinely and non-routinely measured laboratory data. Our framework predicts long-term CV mortality at least as accurate as existing CVD risk scores. A combination of four highly ranked biomarkers and the random forest approach showed the best predictive results. Moreover, a dynamic computational model has several advantages over static CVD risk prediction tools: it is freeware, transparent, variable, transferable and expandable to any population, types of events and time frames. [less ▲]

A Reissner-Mindlin plate formulation using symmetric Hu-Zhang elements via polytopal transformations

E-print/Working paper (2023)

In this work we develop new finite element discretisations of the shear-deformable Reissner--Mindlin plate problem based on the Hellinger-Reissner principle of symmetric stresses. Specifically, we use ... [more ▼]

In this work we develop new finite element discretisations of the shear-deformable Reissner--Mindlin plate problem based on the Hellinger-Reissner principle of symmetric stresses. Specifically, we use conforming Hu-Zhang elements to discretise the bending moments in the space of symmetric square integrable fields with a square integrable divergence. The latter results in highly accurate approximations of the bending moments M and in the rotation field being in the discontinuous Lebesgue space , such that the Kirchhoff-Love constraint can be satisfied for t tending to zero. In order to preserve optimal convergence rates across all variables for the case t tending to zero, we present an extension of the formulation using Raviart-Thomas elements for the shear stress. We prove existence and uniqueness in the continuous setting and rely on exact complexes for inheritance of well-posedness in the discrete setting. This work introduces an efficient construction of the Hu-Zhang base functions on the reference element via the polytopal template methodology and Legendre polynomials, making it applicable to hp-FEM. The base functions on the reference element are then mapped to the physical element using novel polytopal transformations, which are suitable also for curved geometries. The robustness of the formulations and the construction of the Hu-Zhang element are tested for shear-locking, curved geometries and an L-shaped domain with a singularity in the bending moments. Further, we compare the performance of the novel formulations with the primal-, MITC- and recently introduced TDNNS methods. [less ▲]

Interaction of mitochondrial polygenic score and environmental factors in LRRK2 p.Gly2019Ser parkinsonism 2023.01.02.23284113

E-print/Working paper (2023)

The objective of our study was to investigate the impact of the mitochondrial polygenic score (MGS) and lifestyle/environmental data on age at onset in LRRK2 p.Gly2019Ser parkinsonism (LRRK2-PD) and ... [more ▼]

The objective of our study was to investigate the impact of the mitochondrial polygenic score (MGS) and lifestyle/environmental data on age at onset in LRRK2 p.Gly2019Ser parkinsonism (LRRK2-PD) and idiopathic Parkinson\textquoterights disease (iPD).In this study, we included N=486 patients with LRRK2-PD and N=9259 patients with iPD from AMP-PD, Fox Insight, and a Tunisian Arab-Berber founder population. Genotyping data was utilized to perform the MGS analysis, using 14 Single Nucleotide Polymorphisms (SNPs) from genes causally associated with mitochondrial function and PD risk. Additionally, lifestyle and environmental data were obtained from the PD risk factor questionnaire (PD-RFQ). Correlation analyses and linear regression models were used to assess the relationship between MGS, lifestyle/environment, and AAO.We observed that higher MGS was associated with earlier AAO in patients with LRRK2-PD (p=4.0\texttimes10-4, β=-0.18) but not in patients with iPD. A correlation between MGS and AAO was visibly stronger in European ancestry LRRK2-PD patients (p=0.01, r=-0.16) than in Tunisian Arab-Berber patients (p=0.44, r=-0.05). We found that the MGS interacted with coffee (p=0.03, β=-0.38) and caffeinated soda consumption (p=0.03, β=-0.37) in LRRK2-PD and with caffeine soda consumption (p=0.047, β=-0.22) and pesticide exposure (p=0.02, β=-0.37) in iPD. Thus, patients with a high MGS had an earlier AAO only if they consumed caffeine or were exposed to pesticides.The MGS related to mitochondrial function was associated with AAO in LRRK2-PD but not iPD with an ethnic-specific effect. Caffeine consumption or pesticide exposure interacted with MGS to predict PD AAO. Our study suggests gene-environment interactions as modifiers of AAO in LRRK2-PD.Competing Interest StatementCK serves as a medical advisor to Centogene and Retromer Therapeutics and received speaking honoraria from Desitin. The remaining authors declare no conflict of interest.Funding StatementThis project was supported by the DFG RU ProtectMove (DFG FOR2488), the Michael J. Fox Foundation (MJFF-021227 \& MJFF-019271), and the Else Kroener-Fresenius-Stiftung.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethical permission was given by the Ethical Committee of the Institut National de Neurologie and certified by the Ministry of Health, Tunisia.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData sharing is not applicable to this article as no new data were created or analysed in this study. Data used in the preparation of this manuscript were obtained from the Fox Insight database (https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp) on 18/10/2020. For up-to-date information on the study, visit https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp. Data used in the preparation of this article were obtained from the Accelerating Medicine Partnership (AMP) Parkinson\textquoterights Disease (AMP PD) Knowledge Platform. For up-to-date information on the study, visit https://www.amp-pd.org. [less ▲]

On the algebraic immunity of weightwise perfectly balanced functions

E-print/Working paper (2023)

The Impact of the Johnson-Reed Act on Filipino Labor Market Outcomes

E-print/Working paper (2023)

Immigration restrictions to the US are rather modern policies. One of the most significant policy changes, the Johnson-Reed Act of 1924, drastically limited the number of new immigrants per year ... [more ▼]

Immigration restrictions to the US are rather modern policies. One of the most significant policy changes, the Johnson-Reed Act of 1924, drastically limited the number of new immigrants per year, especially from Asia. In combination with the Emergency Quota Act of 1921, immigration per country was capped at 2 percent of the respective population in the 1890 census. In this paper, I examine to what extent immigration restrictions affected labor market outcomes of prior migration cohorts. Using decennial census data, I apply a difference-in-difference estimation, considering that restrictions initially did not impact the Philippines, then a US territory. My findings indicate that initial immigration restrictions affected exempted Filipinos, highlighting the impact of competition on their economic assimilation. Relative to other migrants, labor force participation and employment rates of Filipinos increased while their log income scores declined. This finding corroborates previous studies that emphasize the relevance of substitutability among immigrant cohorts. Individual panel data analysis partially supports the findings in the cross-sectional evaluation. [less ▲]

Closed-End Funds and Discount Control Mechanisms

E-print/Working paper (2023)

The discount control mechanisms that closed-end funds often choose to adopt before IPO are supposedly implemented to narrow the difference between share price and net asset value. We find evidence that ... [more ▼]

The discount control mechanisms that closed-end funds often choose to adopt before IPO are supposedly implemented to narrow the difference between share price and net asset value. We find evidence that non-discretionary discount control mechanisms such as mandatory continuation votes serve as costly signals of information to reveal higher fund quality to investors. Rents of the skill signaled through the announcement of such policies accrue to managers rather than investors as differences in skill are revealed through growing assets under management rather than risk- adjusted performance. [less ▲]

Rose Patterns in the Nonperturbative Current Response of Two-Dimensional Superlattices

E-print/Working paper (2023)

In two-dimensional superlattice materials, the nonlinear current response to a large applied electric field can feature a strong angular dependence. This nonperturbative regime encodes information about ... [more ▼]

In two-dimensional superlattice materials, the nonlinear current response to a large applied electric field can feature a strong angular dependence. This nonperturbative regime encodes information about the band dispersion and Berry curvature of isolated electronic Bloch minibands. Within the relaxation-time approximation, we obtain analytic expressions for the current in a band-projected theory with time-reversal and trigonal symmetry, up to infinite order in the driving field. For a fixed field strength, the dependence of the current on the direction of the applied field is given by rose curves whose petal structure is symmetry constrained and is obtained from an expansion in real-space translation vectors. We illustrate our theory with calculations on periodically-buckled graphene and twisted double bilayer graphene, wherein the discussed physics can be accessed at experimentally-relevant field strengths. [less ▲]

TensAIR: Online Learning from Data Streams via Asynchronous Iterative Routing

E-print/Working paper (2023)

Online learning (OL) from data streams is an emerging area of research that encompasses numerous challenges from stream processing, machine learning, and networking. Recent extensions of stream-processing ... [more ▼]

Online learning (OL) from data streams is an emerging area of research that encompasses numerous challenges from stream processing, machine learning, and networking. Recent extensions of stream-processing platforms, such as Apache Kafka and Flink, already provide basic extensions for the training of neural networks in a stream-processing pipeline. However, these extensions are not scalable and flexible enough for many real-world use-cases, since they do not integrate the neural-network libraries as a first-class citizen into their architectures. In this paper, we present TensAIR, which provides an end-to-end dataflow engine for OL from data streams via a protocol to which we refer as asynchronous iterative routing. TensAIR supports the common dataflow operators, such as Map, Reduce, Join, and has been augmented by the data-parallel OL functions train and predict. These belong to the new Model operator, in which an initial TensorFlow model (either freshly initialized or pre-trained) is replicated among multiple decentralized worker nodes. Our decentralized architecture allows TensAIR to efficiently shard incoming data batches across the distributed model replicas, which in turn trigger the model updates via asynchronous stochastic gradient descent. We empirically demonstrate that TensAIR achieves a nearly linear scale-out in terms of (1) the number of worker nodes deployed in the network, and (2) the throughput at which the data batches arrive at the dataflow operators. We exemplify the versatility of TensAIR by investigating both sparse (Word2Vec) and dense (CIFAR-10) use-cases, for which we are able to demonstrate very significant performance improvements in comparison to Kafka, Flink, and Horovod. We also demonstrate the magnitude of these improvements by depicting the possibility of real-time concept drift adaptation of a sentiment analysis model trained over a Twitter stream. [less ▲]

Mechano-self-regulation of bacterial size in growing colonies

E-print/Working paper (2022)

We demonstrate that biomechanical forcing plays an important role as the driving force behind the dynamical self-regulation of cell size (or length) in growing bacterial colonies. In our experiments, the ... [more ▼]

We demonstrate that biomechanical forcing plays an important role as the driving force behind the dynamical self-regulation of cell size (or length) in growing bacterial colonies. In our experiments, the measured elongation rate decreases over time and depends on the areal packing density around each cell. To describe this phenomenon theoretically, we devise a cell-resolved model which includes as its key ingredient a force opposed to the growth process, accounting for mechano-self-regulation. Our model is analyzed analytically by a coarse-grained dynamical density functional theory and solved by cell-based computer simulations to predict how the strength of mechano-self-regulation depends on the bacterial size, the location in the colony and the local environment. The microscopic nature of this approach allows to quantify the effect of biomechanical interactions on the structure, composition and dynamical features of growing bacterial colonies. [less ▲]

Distributionally robust optimal allocation with costly verification

E-print/Working paper (2022)

Compressive Instabilities Enable Cell-Induced Extreme Densification Patterns in the Fibrous Extracellular Matrix: Discrete Model Predictions

E-print/Working paper (2022)

FastCycle: A Message Sharing Framework for Modular Automated Driving Systems

E-print/Working paper (2022)

Automated Driving Systems (ADS) have rapidly evolved in recent years and their architecture becomes sophisticated. Ensuring robustness, reliability and safety of performance is particularly important. The ... [more ▼]

Automated Driving Systems (ADS) have rapidly evolved in recent years and their architecture becomes sophisticated. Ensuring robustness, reliability and safety of performance is particularly important. The main challenge in building an ADS is the ability to meet certain stringent performance requirements in terms of both making safe operational decisions and finishing processing in real-time. Middlewares play a crucial role to handle these requirements in ADS. The way middlewares share data between the different system components has a direct impact on the overall performance, particularly the latency overhead. To this end, this paper presents FastCycle as a lightweight multi-threaded zero-copy messaging broker to meet the requirements of a high fidelity ADS in terms of modularity, real-time performance and security. We discuss the architecture and the main features of the proposed framework. Evaluation of the proposed framework based on standard metrics in comparison with popular middlewares used in robotics and automated driving shows the improved performance of our framework. The implementation of FastCycle and the associated comparisons with other frameworks are open sourced. [less ▲]

#Discover Life on Mars with a Rover - Didaktischer Kommentar

E-print/Working paper (2022)

Forecasting of a complex microbial community using meta-omics

E-print/Working paper (2022)

Microbial communities are complex assemblages whose dynamics are shaped by abiotic and biotic factors. A major challenge concerns correctly forecasting the community behaviour in the future. In this ... [more ▼]

Microbial communities are complex assemblages whose dynamics are shaped by abiotic and biotic factors. A major challenge concerns correctly forecasting the community behaviour in the future. In this context, communities in biological wastewater treatment plants (BWWTPs) represent excellent model systems, because forecasting them is required to ultimately control and operate the plants in a sustainable manner. Here, we forecast the microbial community from the water-air interface of the anaerobic tank of a BWWTP via longitudinal meta-omics (metagenomics, metatranscriptomics and metaproteomics) data covering 14 months at weekly intervals. We extracted all the available time-dependent information, summarised it in 17 temporal signals (explaining 91.1 of the temporal variance) and linked them over time to rebuild the sequence of ecological phenomena behind the community dynamics. We forecasted the signals over the following five years and tested the predictions with 21 extra samples. We were able to correctly forecast five signals accounting for 22.5 of the time-dependent information in the system and generate mechanistic predictions on the ecological events in the community (e.g. a predation cycle involving bacteria, viruses and amoebas). Through the forecasting of the 17 signals and the environmental variables readings we reconstructed the gene abundance and expression for the following 5 years, showing a nearly perfect trend prediction (coefficient of determination >= 0.97) for the first 2 years. The study demonstrates the maturity of microbial ecology to forecast composition and gene expression of open microbial ecosystems using year-spanning interactions between community cycles and environmental parameters. [less ▲]

Hessian estimates for Dirichlet and Neumann eigenfunctions of Laplacian

E-print/Working paper (2022)

Equivariant elliptic cohomology, toric varieties, and derived equivalences

E-print/Working paper (2022)

Spatio-temporal programming of lyotropic phase transition in nanoporous microfluidic confinements

E-print/Working paper (2022)

Self-assembly of simple molecules into complex phases can be driven by physical constraints, for instance, due to selective molecular uptake by nanoporous surfaces. Despite the significance of surface ... [more ▼]

Self-assembly of simple molecules into complex phases can be driven by physical constraints, for instance, due to selective molecular uptake by nanoporous surfaces. Despite the significance of surface-mediated assembly in evolution of life, physical routes to molecular enrichment and assembly have remained overlooked. Here, using a lyotropic chromonic liquid crystal as model biological material, confined within nanoporous microfluidic environments, we study molecular assembly driven by nanoporous substrates. We demonstrate that nanoporous polydimethylsiloxane (PDMS) surfaces, due to selective permeation of water molecules, drive transition of disordered isotropic phase to ordered nematic, and higher order columnar phases under isothermal conditions. Synergistically, by tailoring the wettability, the surface-to-volume ratio, and surface topography of the confinements, we program the lyotropic phase transitions with a high degree of spatial and temporal control. Using a combination of timelapse polarized imaging, quantitative image processing, and a simple mathematical model, we analyze the phase transitions, and construct a master diagram capturing the role of surface wettability and channel geometry on programmable lyotropic phase transitions. Intrinsic PDMS nanoporosity and confinement cross-section, together with the imposed wettability regulate the rate of the N-M phase transition; whereas the microfluidic geometry and embedded topography enable phase transition at targeted locations. We harness the emergent long-range order during N-M transition to actuate elasto-advective transport of embedded micro-cargo, demonstrating particle manipulation concepts governed by tunable phase transitions. Our results present a programmable physical route to material assembly, and offer a new paradigm for assembling genetic components, biological cargo, and minimal synthetic cells. [less ▲]

Advanced Situational Graphs for Robot Navigation in Structured Indoor Environments

E-print/Working paper (2022)

Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous work, we introduced the ... [more ▼]

Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous work, we introduced the concept of Situation Graphs (S-Graphs) which combines in a single optimizable graph, the robot keyframes and the representation of the environment with geometric, semantic and topological abstractions. Although S-Graphs were built and optimized in real-time and demonstrated state-of-the-art results, they are limited to specific structured environments with specific hand-tuned dimensions of rooms and corridors. In this work, we present an advanced version of the Situational Graphs (S-Graphs+), consisting of the five layered optimizable graph that includes (1) metric layer along with the graph of free-space clusters (2) keyframe layer where the robot poses are registered (3) metric-semantic layer consisting of the extracted planar walls (4) novel rooms layer constraining the extracted planar walls (5) novel floors layer encompassing the rooms within a given floor level. S-Graphs+ demonstrates improved performance over S-Graphs efficiently extracting the room information while simultaneously improving the pose estimate of the robot, thus extending the robots situational awareness in the form of a five layered environmental model. [less ▲]

Integration of external biomass reactions into existing metabolic models

E-print/Working paper (2022)

Currently, seven biomass objective functions have been defined in human metabolic reconstructions. The integration of published biomass reactions into alternative models can contribute to the prediction ... [more ▼]

Currently, seven biomass objective functions have been defined in human metabolic reconstructions. The integration of published biomass reactions into alternative models can contribute to the prediction power of the model. Thus, in this work, we present a workflow to integrate reactions and biomass functions originating from several genome-scale reconstructions into models other than their home models. Additionally, a benchmark to identify the biomass that confers the highest prediction accuracy in terms of gene essentiality and growth predictions is provided. [less ▲]

Local Verlet buffer approach for broad-phase interaction detection in Discrete Element Method

E-print/Working paper (2022)

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties ... [more ▼]

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties such as the thermodynamic state, stress/strain for each particle. Such DEM simulations used by industries to set up their experimental processes are complexes and heavy in computation time. At each time step, those simulations generate a list of interacting particles and this phase is one of the most computationally expensive parts of a DEM simulation. The Verlet buffer method, initially introduced in Molecular Dynamic (MD) (and also used in DEM), allows keeping the interaction list for many time steps by extending each particle neighbourhood by a certain extension range, and thus broadening the interaction list. The method relies on the temporal coherency of DEM, which guarantees that no particles move erratically from one time step to the next. In the classical approach, all the particles have their neighbourhood extended by the same value which leads to suboptimal performances in simulations where different flow regimes coexist. Additionally, and unlike in MD, there is no comprehensive study analysing the different parameters that affect the performance of the Verlet buffer method in DEM. In this work, we propose a new method for the dynamic update of the neighbour list that depends on the particles individual displacement and define a particle-specific extension range based on the local flow regime. The interaction list is analysed throughout the simulation based on the particle's displacement allowing a flexible update according to the flow regime conditions. We evaluate the influence of the Verlet extension range on the execution time through different test cases and analyse empirically the extension range value giving the best performance. [less ▲]

Early-to-mid idiopathic Parkinson’s disease shows a more cytotoxic but declined CD8-regulatory peripheral immune profile

E-print/Working paper (2022)

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Brain neuroinflammation plays a role in PD pathogenesis. However, the involvement of the peripheral immune system has not been ... [more ▼]

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Brain neuroinflammation plays a role in PD pathogenesis. However, the involvement of the peripheral immune system has not been systematically investigated. Here we analyzed >700 combinatorial immunological features in fresh blood of 28 early-to-mid-stage PD patients and 24 matched controls. We found an enhanced cytotoxic immune profile in idiopathic PD patients (iPD), with a higher frequency of terminally-differentiated effector CD8 T (TEMRA), late-differentiated CD8+ natural killer T cells and neutrophils. This immune profile was intensified by elevated serum granzyme A, reduced percentages of CD8+FOXP3+ regulatory T cells and group 2 innate lymphoid cells with immunosuppressive or tolerance-inducing functions. The frequency of CD8 TEMRA was negatively correlated with disease duration, suggesting a contribution to PD pathogenesis. Our work provides a comprehensive map on disturbed peripheral adaptive and innate immune cells in early-to-mid iPD, proposing easily-accessible candidates for early diagnosis and treatments. [less ▲]

Genome-wide meta-analysis of over 29,000 people with epilepsy reveals 26 loci and subtype-specific genetic architecture

E-print/Working paper (2022)

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here, we report a trans-ethnic GWAS including 29,944 cases ... [more ▼]

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here, we report a trans-ethnic GWAS including 29,944 cases, stratified into three broad- and seven sub-types of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants substantially close the missing heritability gap for GGE. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analysis of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current anti-seizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment. [less ▲]

A model-based approach to density estimation in sup-norm

E-print/Working paper (2022)

Building on the l−estimators of Baraud, we define a general method for finding a quasi-best approximant in sup-norm to a target density p⋆ belonging to a given model m, based on independent samples drawn ... [more ▼]

Building on the l−estimators of Baraud, we define a general method for finding a quasi-best approximant in sup-norm to a target density p⋆ belonging to a given model m, based on independent samples drawn from distributions p⋆i which average to p⋆ (which does not necessarily belong to m). We also provide a general method for selecting among a countable family of such models. Both of these esti- mators satisfy oracle inequalities in the general setting. The quality of the bounds depends on the volume of sets C on which |f| is close to its maximum, where f = p − q for some p, q ∈ m (or p ∈ m and q ∈ m′, in the case of model selection). In particular, using piecewise polynomials on dyadic partitions of Rd, we recover optimal rates of convergence for classes of functions with anisotropic smoothness, with optimal depen- dence on semi-norms measuring the smoothness of p⋆ in the coordinate directions. Moreover, our method adapts to the anisotropic smoothness, as long as it is smaller than 1 plus the degree of the polynomials. [less ▲]

Mitochondrial DNA heteroplasmy distinguishes disease manifestation in PINK1- and PRKN-linked Parkinson's disease 2022.05.17.22275087

E-print/Working paper (2022)

Biallelic mutations in PINK1 and PRKN cause recessively inherited Parkinson's disease (PD). Though some studies suggest that PINK1/PRKN monoallelic mutations may not contribute to risk, deep phenotyping ... [more ▼]

Biallelic mutations in PINK1 and PRKN cause recessively inherited Parkinson's disease (PD). Though some studies suggest that PINK1/PRKN monoallelic mutations may not contribute to risk, deep phenotyping assessment showed that PINK1 or PRKN monoallelic pathogenic variants were at a significantly higher rate in PD compared to controls. Given the established role of PINK1 and Parkin in regulating mitochondrial dynamics, we explored mitochondrial DNA (mtDNA) integrity and inflammation as potential disease modifiers in carriers of mutations in these genes. MtDNA integrity, global gene expression and serum cytokine levels were investigated in a large collection of biallelic (n=84) and monoallelic (n=170) carriers of PINK1/PRKN mutations, iPD patients (n=67) and controls (n=90). Affected and unaffected PINK1/PRKN monoallelic mutation carriers can be distinguished by heteroplasmic mtDNA variant load (AUC=0.83, CI:0.74-0.93). Biallelic PINK1/PRKN mutation carriers harbor more heteroplasmic mtDNA variants in blood (p=0.0006, Z=3.63) compared to monoallelic mutation carriers. This enrichment was confirmed in iPSC-derived and postmortem midbrain neurons from biallelic PRKN-PD patients. Lastly, the heteroplasmic mtDNA variant load was found to correlate with IL6 levels in PINK1/PRKN mutation carriers (r=0.57, p=0.0074). PINK1/PRKN mutations predispose individuals to mtDNA variant accumulation in a dose- and disease-dependent manner. MtDNA variant load over time is a potential marker of disease manifestation in PINK1/PRKN mutation carriers.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe authors wish to thank the many patients and their families who volunteered, and the efforts of the many clinical teams involved. Funding has been obtained from the German Research Foundation (ProtectMove; FOR 2488, GR 3731/5-1; SE 2608/2-1; KO 2250/7-1), the Luxembourg National Research Fund in the ATTRACT (Model-IPD, FNR9631103), NCER-PD (FNR11264123) and INTER programmes (ProtectMove, FNR11250962; MiRisk-PD, C17/BM/11676395, NB 4328/2-1), the BMBF (MitoPD), the Hermann and Lilly Schilling Foundation, the European Community (SysMedPD), the Canadian Institutes of Health Research (CIHR), Peter and Traudl Engelhorn Foundation. Initial studies in Tunisia on familial parkinsonism were in collaboration with Lefkos Middleton, Rachel Gibson, and the GlaxoSmithKline PD Programme Team (2002-2005). We would like to thank Dr Helen Tuppen from the Welcome Trust Centre for Mitochondrial Research, Newcastle University, UK for providing us with the plasmid p7D1. Moreover, this project was supported by the high throughput/high content screening platform and HPC facility at the Luxembourg Centre for Systems Biomedicine, and the University of Luxembourg.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:University of Lubeck Ethics CommitteeI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors [less ▲]

Erinnerungspolitik und –praxis in Luxemburg am Beispiel einer gegenwärtigen Kontroverse

E-print/Working paper (2022)

In September 2021, so-called stumbling blocks were set by a Luxembourg school class: four for Jewish people who were murdered in concentration camps and eleven for young men who were forcibly drafted into ... [more ▼]

In September 2021, so-called stumbling blocks were set by a Luxembourg school class: four for Jewish people who were murdered in concentration camps and eleven for young men who were forcibly drafted into the Wehrmacht and died in the war. The commemoration triggered a broadly received controversy, which this article aims to explain and contextualize. [less ▲]

Creating Public History Master Programs: International Guidelines

E-print/Working paper (2022)

Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets

E-print/Working paper (2022)

Federated learning allows clients to collaboratively train models on datasets that are acquired in different locations and that cannot be exchanged because of their size or regulations. Such collected ... [more ▼]

Federated learning allows clients to collaboratively train models on datasets that are acquired in different locations and that cannot be exchanged because of their size or regulations. Such collected data is increasingly non-independent and non- identically distributed (non-IID), negatively affecting training accuracy. Previous works tried to mitigate the effects of non- IID datasets on training accuracy, focusing mainly on non-IID labels, however practical datasets often also contain non-IID features. To address both non-IID labels and features, we propose FedGMCC1, a novel framework where a central server aggregates client models that it can cluster together. FedGMCC clustering relies on a Monte Carlo procedure that samples the output space of client models, infers their position in the weight space on a loss manifold and computes their geometric connection via an affine curve parametrization. FedGMCC aggregates connected models along their path connectivity to produce a richer global model, incorporating knowledge of all connected client models. FedGMCC outperforms FedAvg and FedProx in terms of convergence rates on the EMNIST62 and a genomic sequence classification datasets (by up to +63%). FedGMCC yields an improved accuracy (+4%) on the genomic dataset with respect to CFL, in high non-IID feature space settings and label incongruency. [less ▲]

Quasi-Fuchsian manifolds close to the Fuchsian locus are foliated by constant mean curvature surfaces

E-print/Working paper (2022)

An overview of the Eight International Olympiad in Cryptography "Non-Stop University CRYPTO"

E-print/Working paper (2022)

Non-Stop University CRYPTO is the International Olympiad in Cryptography that was held for the eight time in 2021. Hundreds of university and school students, professionals from 33 countries worked on ... [more ▼]

Non-Stop University CRYPTO is the International Olympiad in Cryptography that was held for the eight time in 2021. Hundreds of university and school students, professionals from 33 countries worked on mathematical problems in cryptography during a week. The aim of the Olympiad is to attract attention to curious and even open scientific problems of modern cryptography. In this paper, problems and their solutions of the Olympiad’2021 are presented. We consider 19 problems of varying difficulty and topics: ciphers, online machines, passwords, binary strings, permutations, quantum circuits, historical ciphers, elliptic curves, masking, implementation on a chip, etc. We discuss several open problems on quantum error correction, finding special permutations and s-Boolean sharing of a function, obtaining new bounds on the distance to affine vectorial functions. [less ▲]

Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes 2022.03.23.485339

E-print/Working paper (2022)

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 ... [more ▼]

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 novel 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5 A 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 fucntional 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 neurodevelopmental disorder pathogenic patient variants, and 679 electrophysiological experiments that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain vs. loss-of-channel function.In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional read-outs and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.Competing Interest StatementThe authors have declared no competing interest.DSSPDictionary of Protein Secondary StructuregnomADGenome aggregation DatabaseGoFGain of functionGRIN genesGRIN1, GRIN2A. GRIN2BHGMDHuman Gene Mutation DatabaseNMDA receptorN-methyl-D-aspartate receptorGABA receptorGamma-aminobutyric acid receptorLoFLoss of functionSCN genesSCN1A, SCN2A, SCN8AVCFVariant Call Format [less ▲]

POTENTIAL METHOD AND PROJECTION THEOREMS FOR MACROSCOPIC HAUSDORFF DIMENSION

E-print/Working paper (2022)

Supercurrent-enabled Andreev reflection in a chiral quantum Hall edge state

E-print/Working paper (2022)