The field of quantum computing and information theory is rapidly advancing, with a focus on developing innovative solutions to complex problems. Researchers are exploring new techniques for physical layer authentication, Doppler-resilient complementary sequences, and fast Shannon entropy approximation. Additionally, there is a growing interest in quantum-inspired neural networks, hybrid quantum swarm intelligence, and quantum-evolutionary neural networks for multi-agent federated learning. These advancements have the potential to significantly impact various fields, including communication systems, machine learning, and cryptography. Noteworthy papers in this area include: Enhanced Multiuser CSI-Based Physical Layer Authentication Based on Information Reconciliation, which presents a cost-effective solution for low-end Internet of Things networks. Fast and close Shannon entropy approximation, which achieves a mean absolute error of 10^-3 and allows for around 50% faster computation. RISC-Q: A Generator for Real-Time Quantum Control System-on-Chip, which enables efficient automation of highly parameterized and modular QCSoC architectures. HQSI: Hybrid Quantum Swarm Intelligence, which constructs a QNN model as a forward propagation neural network and achieves more than a 50% reduction in error. Quantum-Evolutionary Neural Networks for Multi-Agent Federated Learning, which leverages quantum computing principles to enhance learning speed and decision accuracy. A Quantum-Enhanced Power Flow and Optimal Power Flow based on Combinatorial Reformulation, which utilizes a novel combinatorial optimization reformulation of classical PF and OPF problems. Extensible Post Quantum Cryptography Based Authentication, which introduces a quantum-safe single-shot protocol for machine-to-machine authentication and authorization. Half-Marker Codes for Deletion Channels with Applications in DNA Storage, which proposes a new class of marker codes that can significantly increase the mutual information between the input symbols and the soft outputs of an IDS channel. Energy Consumption Framework and Analysis of Post-Quantum Key-Generation on Embedded Devices, which introduces a new framework for measuring the PQC energy consumption on embedded devices. Quantum Feature Optimization for Enhanced Clustering of Blockchain Transaction Data, which conducts a comparative analysis of three clustering approaches and demonstrates that even shallow quantum circuits can effectively extract meaningful non-linear representations.