ChatGPT: a pedagogical use case

Presentation (2023, February 01)

Energy-Efficient Backscatter Aided Uplink NOMA Roadside Sensor Communications under Channel Estimation Errors

in IEEE Transactions on Intelligent Transportation Systems (2023)

This work presents non-orthogonal multiple access (NOMA) enabled energy-efficient alternating optimization framework for backscatter aided wireless powered uplink sensors communications for beyond 5G ... [more ▼]

This work presents non-orthogonal multiple access (NOMA) enabled energy-efficient alternating optimization framework for backscatter aided wireless powered uplink sensors communications for beyond 5G intelligent transportation system (ITS). Specifically, the transmit power of carrier emitter (CE) and reflection coefficients of backscatter aided roadside sensors are optimized with channel uncertainties for the maximization of the energy efficiency (EE) of the network. The formulated problem is tackled by the proposed two-stage alternating optimization algorithm named AOBWS (alternating optimization for backscatter aided wireless powered sensors). In the first stage, AOBWS employs an iterative algorithm to obtain optimal CE transmit power through simplified closed-form computed through Cardano’s formulae. In the second stage, AOBWS uses a noniterative algorithm that provides a closed-form expression for the computation of optimal reflection coefficient for roadside sensors under their quality of service (QoS) and a circuit power constraint. The global optimal exhaustive search (ES) algorithm is used as a benchmark. Simulation results demonstrate that the AOBWS algorithm can achieve near-optimal performance with very low complexity, which makes it suitable for practical implementations. [less ▲]

Policy Brief to the French Public Consultation on Influencers and Content Creators

Diverse speeches and writings (2023)

Arbitrage bots in experimental asset markets

in Journal of Economic Behavior and Organization (2023), 206

Trading algorithms are an integral component of modern asset markets. In twin experimental markets for long-lived correlated assets we examine the impact of alternative types of arbitrage-seeking ... [more ▼]

Trading algorithms are an integral component of modern asset markets. In twin experimental markets for long-lived correlated assets we examine the impact of alternative types of arbitrage-seeking algorithms. These arbitrage robot traders vary in their latency and whether they make or take market liquidity. All arbitrage robot traders we examine generate greater conformity to the law-of-one-price across the twin markets. However, only the liquidity providing arbitrage robot trader moves prices into closer alignment with fundamental values. The reduced mispricing comes with varying social costs; arbitrage robot traders’ gains reduce the earnings of human traders. We identify factors which drive differences in human trader performance and find that the presence of an arbitrage robot trader has no disproportionate effect with respect to these factors on subjects’ earnings. [less ▲]

Automatisierter öffentlicher Verkehr in Grenzregionen

in Internationales Verkehrswesen (2023)

Wahrnehmung von Zusammenhalt aus Sicht von Menschen mit und ohne Behinderungserfahrungen. Erhebungsdesign und erste (Lern-)Erfahrungen des Projekts ZuSicht

Presentation (2023, February)

DenseQMC: an efficient bit-slice implementation of the Quine-McCluskey algorithm

E-print/Working paper (2023)

This note describes a new efficient bit-slice implementation DenseQMC of the Quine-McCluskey algorithm for finding all prime implicants of a Boolean function in the dense case. It is practically feasible ... [more ▼]

This note describes a new efficient bit-slice implementation DenseQMC of the Quine-McCluskey algorithm for finding all prime implicants of a Boolean function in the dense case. It is practically feasible for n <= 23 when run on a common laptop or for n <= 27 when run on a server with 1 TiB RAM. This note also outlines a very common mistake in the implementations of the Quine-McCluskey algorithm, leading to a quadratic slowdown. An optimized corrected implementation of the classic approach is also given (called SparseQMC). The implementation is freely available at https://github.com/hellman/Quine-McCluskey . [less ▲]

IDEA Heuristics: A guided checklist for Evaluating the Usability of Educational E-assessments with Children

Presentation (2023, February)

Consonant and Dissonant Experiences—Young Migrants’ Un-derstandings of Integration: A Cross-Country Comparison between Germany, Luxembourg, and Norway.

in Social Sciences (2023), 12

Our article addresses two aspects of young migrants’ understandings of integration: their own ideas of what integration is, and their perception of the destination society’s concepts and expectations ... [more ▼]

Our article addresses two aspects of young migrants’ understandings of integration: their own ideas of what integration is, and their perception of the destination society’s concepts and expectations regarding their integration. We analyze qualitative interviews which were conducted in the Horizon 2020 project MIMY, in Germany, Luxembourg and Norway, using the grounded theory methodology. Our exploration shows that the young migrants’ awareness of the existing ideas of integration surrounding them creates a complex reflective interaction between their own ideas and the (perceived) expectations from society. We identified aspects of consonance, where young migrants’ ideas coincide with the expectations they perceive. More importantly, however, our research has discovered that the youth experience tensions and dissonance between their own ideas of what integration should be and the concepts and expectations regarding integration they feel confronted with by society. Our analysis revealed that while young migrants’ understandings of integration are very close to state-of-the-art scientific conceptualizations of integration, this view is not matched by the meaning of integration they perceive around them. [less ▲]

Applications of Boolean modelling to study and stratify dynamics of a complex disease

Doctoral thesis (2023)

Interpretation of omics data is needed to form meaningful hypotheses about disease mechanisms. Pathway databases give an overview of disease-related processes, while mathematical models give qualitative ... [more ▼]

Interpretation of omics data is needed to form meaningful hypotheses about disease mechanisms. Pathway databases give an overview of disease-related processes, while mathematical models give qualitative and quantitative insights into their complexity. Similarly to pathway databases, mathematical models are stored and shared on dedicated platforms. Moreover, community-driven initiatives such as disease maps encode disease-specific mechanisms in both computable and diagrammatic form using dedicated tools for diagram biocuration and visualisation. To investigate the dynamic properties of complex disease mechanisms, computationally readable content can be used as a scaffold for building dynamic models in an automated fashion. The dynamic properties of a disease are extremely complex. Therefore, more research is required to better understand the complexity of molecular mechanisms, which may advance personalized medicine in the future. In this study, Parkinson’s disease (PD) is analyzed as an example of a complex disorder. PD is associated with complex genetic, environmental causes and comorbidities that need to be analysed in a systematic way to better understand the progression of different disease subtypes. Studying PD as a multifactorial disease requires deconvoluting the multiple and overlapping changes to identify the driving neurodegenerative mechanisms. Integrated systems analysis and modelling can enable us to study different aspects of a disease such as progression, diagnosis, and response to therapeutics. Therefore, more research is required to better understand the complexity of molecular mechanisms, which may advance personalized medicine in the future. Modelling such complex processes depends on the scope and it may vary depending on the nature of the process (e.g. signalling vs metabolic). Experimental design and the resulting data also influence model structure and analysis. Boolean modelling is proposed to analyse the complexity of PD mechanisms. Boolean models (BMs) are qualitative rather than quantitative and do not require detailed kinetic information such as Petri nets or Ordinary Differential equations (ODEs). Boolean modelling represents a logical formalism where available variables have binary values of one (ON) or zero (OFF), making it a plausible approach in cases where quantitative details and kinetic parameters 9 are not available. Boolean modelling is well validated in clinical and translational medicine research. In this project, the PD map was translated into BMs in an automated fashion using different methods. Therefore, the complexity of disease pathways can be analysed by simulating the effect of genomic burden on omics data. In order to make sure that BMs accurately represent the biological system, validation was performed by simulating models at different scales of complexity. The behaviour of the models was compared with expected behavior based on validated biological knowledge. The TCA cycle was used as an example of a well-studied simple network. Different scales of complex signalling networks were used including the Wnt-PI3k/AKT pathway, and T-cell differentiation models. As a result, matched and mismatched behaviours were identified, allowing the models to be modified to better represent disease mechanisms. The BMs were stratified by integrating omics data from multiple disease cohorts. The miRNA datasets from the Parkinson’s Progression Markers Initiative study (PPMI) were analysed. PPMI provides an important resource for the investigation of potential biomarkers and therapeutic targets for PD. Such stratification allowed studying disease heterogeneity and specific responses to molecular perturbations. The results can support research hypotheses, diagnose a condition, and maximize the benefit of a treatment. Furthermore, the challenges and limitations associated with Boolean modelling in general were discussed, as well as those specific to the current study. Based on the results, there are different ways to improve Boolean modelling applications. Modellers can perform exploratory investigations, gathering the associated information about the model from literature and data resources. The missing details can be inferred by integrating omics data, which identifies missing components and optimises model accuracy. Accurate and computable models improve the efficiency of simulations and the resulting analysis of their controllability. In parallel, the maintenance of model repositories and the sharing of models in easily interoperable formats are also important. [less ▲]