Rubric: Technical sciences

Annotation: The progressive retirement of legacy cellular technologies represents one of the most intricate operational challenges faced by contemporary mobile network operators. While the migration toward LTE and fifth-generation infrastructures has been widely documented, the methodological foundations governing the controlled sunset of earlier radio access technologies remain comparatively underexplored. In particular, the decommissioning of UMTS networks introduces a complex interplay between spectrum refarming, traffic redistribution, service continuity, and operational risk. If performed without analytical guidance, the shutdown of legacy radio layers may provoke severe congestion phenomena, localized capacity collapse, and degradation of user-perceived service quality. This study proposes a structured analytical framework for strategic UMTS sunset implementation within national-scale mobile networks. The research develops a mathematical model that conceptualizes technology retirement not as an isolated operational procedure but as a multi-stage optimization problem embedded within the broader dynamics of traffic migration and spectrum reallocation. The model integrates probabilistic risk estimation, predictive traffic forecasting, and performance-oriented optimization in order to determine the most balanced trajectory of legacy infrastructure decommissioning. To validate the analytical model, a dedicated experimental software environment was implemented in Python, enabling simulation of progressive UMTS shutdown scenarios and comparative evaluation of alternative decision strategies. The system incorporates modules for dataset preprocessing, predictive traffic modeling, iterative sunset simulation, and analytical visualization of network behavior. An openly available dataset describing cellular network performance indicators was used to construct a synthetic yet statistically plausible representation of sector-level radio conditions. Simulation results demonstrate that risk-aware sunset strategies significantly reduce the probability of network overload events while preserving higher LTE throughput levels during the transition process. In contrast, load-driven or stochastic shutdown strategies exhibit increased susceptibility to blackout conditions under heavy traffic migration scenarios. The obtained findings indicate that integrating predictive modeling and probabilistic risk assessment into sunset planning procedures enables a more stable and resource-efficient transformation of cellular infrastructures. The proposed methodological framework contributes to the emerging body of research on technological transitions in mobile networks by providing a coherent analytical approach to legacy technology retirement. Beyond its theoretical implications, the model may serve as a practical decision-support instrument for mobile operators planning large-scale spectrum refarming and infrastructure modernization initiatives.

Annotation: The traditional response is almost always too late. The very nature of the crisis is changing. It’s faster now. More unpredictable. And our old tools simply can't keep up. When disaster hits, time is everything. And we lose it. Every single time. We lose it while rescue teams are stuck, fighting through ruined roads. And every minute wasted is a life. And here’s the paradox, the author argues. The very tech we associate with destruction — drones — is becoming our single most powerful tool for rescue. This article lays out a new playbook. It’s not just about tech, it’s a new way of thinking. A playbook where drones get there first. First eyes on the disaster. First hands delivering life-saving aid. The first signal reconnecting a world gone dark. The author's methodology isn't just about 'launching a drone.' No. It's about a complete, integrated architecture. This isn't about replacing people. It’s about empowering them. It ties together scouting, logistics, documentation... and—this is key—the ethical rules of the game. This isn't a theory. This system was born from real-world experience, where it's already proven its worth. So, how does it work? It's not magic, it's a clear structure. The author breaks it down into four key parts. Drones for initial assessment. Drones for evacuation and delivery. Drones as a tool for objective documentation. And finally, strict ethical standards to keep it all in check. Bottom line? This model isn't just a tech showcase. It's a shot at rewriting the first few, critical hours after a disaster hits. Turning to waiting and uncertainty... into active, smart, life-saving action. It's about giving people a chance. A chance they never had before.

Annotation: In today's energy system, where renewable energy is actively developing, Energy Storage Systems (ESS) are becoming particularly important. A promising direction for ensuring the reliable and uninterrupted operation of energy systems in the United States (US) is modern approaches to the integration of solar energy generation systems (PV generation) and pumped storage power plants. The study analyzed the technical characteristics of a strategic integration model, its advantages, and potential limitations using the example of Southern Nevada. The article presents key concepts of the economic rationale for integrating PV generation and pumped storage power plants for US energy security. It is argued that the combination of pumped storage and PV generation can effectively smooth out fluctuations in renewable energy generation and cover peak loads, increasing the flexibility and resilience of the power system.

Annotation: The article addresses the challenge of automating architectural quality control in microservice systems designed using Domain-Driven Design methodology. A comparative analysis of the effectiveness of deterministic methods and probabilistic methods was conducted. Using a simulated e-commerce system with a controlled set of defects, a quantitative assessment of Precision and Recall metrics was performed for both approaches. The experiment confirmed that deterministic methods ensure absolute precision in detecting structural boundary violations but exhibit "semantic blindness" regarding complex DDD patterns. Conversely, probabilistic methods demonstrated high effectiveness in identifying semantic defects, such as anemic domain models and context leakage, with an acceptable level of false positives. Based on the results, the necessity of implementing a hybrid verification strategy is substantiated, where static analysis acts as a rigid gatekeeper in CI/CD pipelines, while AI tools serve as an intelligent architect's assistant.