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The world modelling newswire

What is happening worldwide in digital twins, mathematical modelling and the management of large-scale systems: research, press releases, product news. From the US, China, ASEAN and Africa — translated and summarised.

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179 items

ForecastingUS & West

Stochastic Nonlinear MPC with Gaussian Mixture Uncertainty Propagation

A new stochastic nonlinear model predictive control method for systems with additive noise is proposed. State distribution is approximated by Gaussian mixture with error bounds in Wasserstein distance. This yields closed-form expressions for expected costs and chance constraints, and the problem is solvable via nonlinear programming with correctness guarantees.

Market & products

US Nurses Protest Against Hospital Contracts with Palantir

Coordinated protests against Palantir took place in eight US cities, organized by nurses, patients, and activists. They demand that hospitals and authorities terminate contracts with Palantir due to concerns about surveillance, including its use by immigration services, and the company's growing presence in healthcare.

ModellingUS & West

Mechanics of Democratic Dominance: System Dynamics for Consent Engineering

A new interdisciplinary paradigm, Dynamic Consent Engineering (DCE), is introduced, synthesizing Edward Bernays' principles of public relations with the S-E-E-D (Snowball, Equilibrium, Elasticity, Dominance) framework of system dynamics. The authors expand Bernaysian operational constraints into a four-dimensional resource matrix incorporating algorithmic media infrastructure and mathematically formalize how democratic institutions construct, optimize, and sustain political dominance.

ForecastingUS & West

Distributed MPC for Optimal Consensus of Heterogeneous Multi-Agent Systems

The paper addresses the distributed optimal consensus control problem for constrained heterogeneous multi-agent systems within a model predictive control (MPC) framework. The approach optimizes both the control input sequence and the dynamically feasible consensus equilibrium simultaneously, resulting in a coupled optimization problem at each prediction step. A distributed primal-dual algorithm is developed, and locally verifiable conditions for its convergence are derived. Sufficient terminal conditions are established to guarantee recursive feasibility and asymptotic consensus of the closed-loop system.

EnergyUS & West

Initialization Is Key in Federated Short-Term Load Forecasting

The study focuses on federated learning for short-term load forecasting (STLF), addressing data privacy concerns. The authors identify structured heterogeneity in clients' load data: different responses to exogenous factors and distinct temporal load profiles, which degrade forecasting performance in federated learning. To mitigate these issues, they propose two model initialization strategies — global and local — that improve forecasting accuracy.

Digital twinUS & West

Digital Twin for Reliable Vessel Localization in Sliding Palpation

A robot-assisted sliding palpation system uses a calibrated digital twin to generate labeled tactile sequences, reducing reliance on real-world data. The model of sensor-vessel contact is calibrated using Bayesian optimization against real palpation trajectories. A spatio-temporal graph neural network trained on simulated marker trajectories performs vessel classification and creates a localisation map.

Digital twinUS & West

A Trans-Domain Digital Twin for Bio-Aware Climate and Energy Control in Cattle Barns

A trans-domain digital twin framework is proposed for closed cattle barns, integrating a climate simulator, livestock growth simulator, model predictive control, and lightweight reinforcement learning. It captures the mutual influence of microclimate and animal growth, enabling optimized conditions and energy use.