The field of algorithms is experiencing significant growth, with a focus on developing innovative solutions to complex problems. Recent research has explored the expansion of the notion of algorithm, including probabilistic and quantum algorithms, and the introduction of more ambitious versions of the Church-Turing thesis. There is also a growing interest in developing fast parallel processing algorithms, with a particular emphasis on asynchronous execution and convergence without synchronization. Additionally, researchers are working on improving the efficiency of distributed algorithms, including average consensus problems in open multi-agent systems and bandwidth-limited directed networks. Noteworthy papers in this area include: Distributed Quantized Average Consensus in Open Multi-Agent Systems with Dynamic Communication Links, which presents a distributed algorithm for calculating the quantized average of initial states in open dynamic multi-agent systems. Convergence Sans Synchronization, which develops a theory for guaranteeing convergence in asynchronous multiprocessor algorithms. Average Consensus with Dynamic Compression in Bandwidth-Limited Directed Networks, which proposes a distributed consensus algorithm with adaptive quantization for achieving convergence to the exact average in directed unbalanced networks.