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.
187 items
At the 20th anniversary of the Korea-Africa Economic Cooperation (KOAFEC), Korea and Africa charted a new course for cooperation on artificial intelligence and digital infrastructure. Details of agreements were not disclosed.
A prototype system has been developed where EPICS controls beam optics simulations for the CEBAF injector, with the simulation running locally or remotely. The system models a beamline with dozens of magnets and diagnostic devices.
A concept for a digital twin of a mouse is proposed as an embodied dynamical system unifying neural activity, biomechanics, sensory feedback, and environmental interactions. Construction relies on CT, anatomical sections, and Scx-GFP imaging, along with Bonhoeffer-van der Pol neural dynamics.
Investigates how many training pilots are needed when a digital twin of a wireless channel is used for channel estimation. The twin is treated as a complementary measurement fused with pilot observations. For the first time, this trade-off is formalized and quantified.
The article discusses an architecture of a digital twin for nuclear systems, integrating multiple models (physics-based and data-driven) to support decision making, state estimation, predictive control, and real-time data processing. The twin must synchronize with the physical facility faster than its operational cycle.
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.
The company 'Aktiv' has finalized a document based on the foresight session held in Moscow in March 2025. The document includes strategic recommendations and forecasts for the industry development until 2040.
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.
Digital Sector, having launched a practice of integrating AI components into custom web systems, is expanding it with corporate agentic scenarios. Details are not disclosed, but it implies the use of an agent-based approach in corporate AI solutions.
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.
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.
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.
A method for channel modeling based on satellite imagery for 6G communication digital twins is proposed. The framework includes deterministic ray tracing, statistical processing, and RT augmentation, enabling channel models for large areas without detailed 3D maps.
A framework Spec2Twin-Chain for automated construction of blockchain digital twins is presented. The process is formulated as bi-level optimization where an LLM proposes and revises architectures based on specifications and behavioral data. Aimed at improving reuse and simplifying twin creation.
A hierarchical digital twin framework for a machine tool is presented, including real-time twins of the machine and the machining process. It integrates CNC data, voxel-based workpiece representation, vibration measurements, and a part repository for traceability and synthetic data generation.
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.
The paper presents an approach to formal verification of digital twin (DT) qualities in systems-of-systems (SoS). The authors use a case study of a greenhouse SoS modeled in VDM-RT, with executable formal models and property-based account of DT qualities. Obstacles to composing these artifacts at the SoS level are analyzed.
COMSOL is advancing integration of multiphysics simulation with digital twin technologies. This enables more accurate and comprehensive models for industrial and engineering applications.
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.
