The field of numerical integration and control of dynamical systems is experiencing significant developments, with a focus on improving the accuracy and efficiency of numerical methods. Researchers are exploring new approaches to integrate dynamical systems while preserving their inherent properties, such as first integrals and symplecticity. Additionally, there is a growing interest in verifying the contractivity of learning-based controllers and developing physically consistent Lagrangian control models. The use of advanced numerical methods, such as variational integrators and material point methods, is becoming increasingly popular for simulating complex systems, including those with friction and nonlinear dynamics. Noteworthy papers include: Feedback Integrators Revisited, which provides a significant improvement to the Feedback Integrator framework, and Verifying Closed-Loop Contractivity of Learning-Based Controllers via Partitioning, which proposes a tractable and scalable sufficient condition for closed-loop contractivity. Learning Physically Consistent Lagrangian Control Models Without Acceleration Measurements is also noteworthy, as it investigates the modeling and control of Lagrangian systems involving non-conservative forces using a hybrid method that does not require acceleration calculations.