The field of numerical methods and algorithms is witnessing significant advancements, with a focus on developing efficient and innovative solutions to complex problems. Researchers are exploring new approaches to improve the accuracy and performance of various numerical methods, including the solution of linear equations, eigenvalue problems, and beam equations. Additionally, there is a growing interest in the development of preconditioners for covariance matrices and the application of beyond-worst-case analysis in symbolic computation. Noteworthy papers in this area include: On the Inversion Modulo a Power of an Integer, which proposes an efficient algorithm for computing modular inverses, and Beyond Worst-Case Analysis for Symbolic Computation: Root Isolation Algorithms, which introduces a smoothed analysis framework for polynomials with integer coefficients. These advancements have the potential to impact various fields, including computer science, mathematics, and engineering.