The field of numerical methods for fluid dynamics and related fields is experiencing significant developments, with a focus on improving the accuracy, stability, and efficiency of simulations. One of the key directions is the development of structure-preserving numerical methods, which ensure that the numerical solution satisfies the same physical laws and conservation principles as the underlying continuous problem. This includes the development of entropy-stable, kinetic energy-preserving, and thermodynamically compatible schemes. Another important area of research is the development of reduced order models (ROMs) and model reduction techniques, which aim to reduce the computational cost of simulations while maintaining their accuracy. The use of tensor-based methods and Petrov-Galerkin projections is also becoming increasingly popular for model reduction and joint reduction of state order and scheduling signal dimension. Noteworthy papers in this area include: A Hybrid Particle-Continuum Method for Simulating Fast Ice via Subgrid Iceberg Interaction, which proposes a novel subgrid-scale coupling mechanism between Lagrangian iceberg particles and an Eulerian sea-ice continuum model. The paper A generalized ENO reconstruction in compact GKS for compressible flow simulations presents a generalized ENO-type nonlinear reconstruction scheme for compressible flow simulations, which provides an optimal transition between linear and nonlinear reconstructions across all limiting cases. The paper Efficient Adjoint Petrov-Galerkin Reduced Order Models for fluid flows governed by the incompressible Navier-Stokes equations introduces a new efficient Adjoint Petrov-Galerkin ROM formulation, which extends its application to the incompressible Navier-Stokes equations by exploiting the polynomial structure inherent in these equations.