Relays are pivotal in military communication networks, expanding coverage and ensuring reliable connectivity in challenging operational environments. While traditional terrestrial relays (TR) are constrained by fixed locations and vulnerability to physical obstructions, unmanned aerial vehicle (UAV)-mounted aerial relays (AR) offer a dynamic and flexible alternative by operating above obstacles and adapting to changing battlefield conditions. This paper provides a comprehensive survey of AR systems in military communications, presenting a detailed comparison between AR and TR paradigms and examining two specific AR technologies: active aerial relays (AAR) and aerial reconfigurable intelligent surface (ARIS) relays. The survey delves into their operation, benefits, challenges, and military applications, supported by a qualitative analysis across metrics such as coverage, flexibility, security, and cost. A novel multi-dimensional metric, the mission-critical relay effectiveness score (MCRES), is introduced as a quantitative method for evaluating relay suitability based on mission-specific weights for critical attributes like mobility, jamming resilience, deployment speed, stealth, coverage, and autonomy. Furthermore, we present Algorithm 1, a decision-making framework that leverages the MCRES to guide the systematic selection of the optimal relay type, AR or TR, and subsequently AAR or ARIS, tailored to the unique demands of a given military scenario, such as dynamic battlefield operations, electronic warfare, or covert missions. Finally, the paper addresses current implementation challenges and outlines promising future research directions to advance the deployment of robust and resilient UAV-mounted relay systems in contested military environments.
For finite dimensional algebras over algebraically closed fields, we study the sets of pairwise Hom-orthogonal modules and obtain new results on some open conjectures on the behaviour of bricks and several related problems, which we generally refer to as brick-Brauer-Thrall (bBT) conjectures. Using some algebraic and geometric tools, and in terms of the notion of Hom-orthogonality, we find necessary and sufficient conditions for the existence of infinite families of bricks of the same dimension. This sheds new light on the bBT conjectures and we prove some of them for new families of algebras. Our results imply some interesting algebraic and geometric characterizations of brick-finite algebras as conceptual generalizations of local algebras. We also verify the bBT conjectures for any algebra whose Auslander-Reiten quiver has a generalized standard component, which particularly extends some results of Chindris-Kinser-Weyman on the algebras with preprojective components. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PURPOSE:Co-leadership between physicians and senior managers is being explored as an avenue to improve decision processes and ensure support of orientations. Reaching those objectives depends partly on the role played by physician co-leaders, a role crafted through ongoing negotiation between actors attempting to expand or constrict the role. The study aims to contribute insight into how physicians entering senior co-leadership roles, and those around them, craft their roles. DESIGN/METHODOLOGY/APPROACH:A qualitative, inductive study of new senior co-leadership roles for physicians in four healthcare centers in Quebec, Canada, was conducted over 21 months, involving interviews, observations and document analysis. FINDINGS:A total of 16 practices mobilized by actors to expand and/or constrict the new roles are identified, revealing that role crafting can occur by creating emptiness in one's role or adjacent roles, by shaping other actors' agency and by influencing processes. PRACTICAL IMPLICATIONS:During the early phases of implementation of co-leadership, attention should be paid to agency and processes, since much role crafting can be done through others or by refraining from exerting influence. A balanced level of cultural sensitivity is more important than a unified culture, and a positioning exercise should be conducted to contemplate the new role relative to its wider organizational leadership context, beyond the dyad. ORIGINALITY/VALUE:The study suggests that the shared role of co-leaders, during the early phases of implementation of co-leadership, is much more vulnerable than portrayed in previous work, overlapping with other constellations and subject to significant intervention from outside the dyad itself.
We report a comprehensive set of direct numerical simulation benchmarks of bypass transition in the narrow sense with inlet freestream turbulent intensity levels 0.75%, 1.5%, 2.25%, 3.0%, and 6.0%, respectively. Detailed descriptions of length scales and the rate of viscous dissipation are provided. We address two key physical questions. First, how do the decay rates and length scales of freestream turbulence over a transitional and turbulent boundary layer compare to those in spatially developing isotropic turbulence without the wall? Second, what bypass mechanisms drive turbulent spot inception at the intermediate range of freestream turbulence intensity level? We find that the boundary-layer freestream turbulence decay and length scales evolve similarly to their spatially developing isotropic turbulence flow without the wall counterparts. We also present evidence of the coexistence of two turbulent spot inception mechanisms at the inlet FST level 2.25%: the long low-speed streak primary and secondary instabilities (only in lower inlet FST levels) and the self-amplifying process of oblique vortex filaments interacting with a A-shaped low-speed patch underneath (prevailing only in higher inlet FST levels).
Tiny Machine Learning (TinyML) enables intelligent inference on resource-constrained edge devices, positioning it as a cornerstone for sixth-generation (6G) wireless systems demanding ubiquitous, low-latency, distributed intelligence at unprecedented scale. However, TinyML development is significantly constrained by limited availability of representative datasets and absence of standardized benchmarking protocols aligned with 6G requirements. This survey analyzes 12 representative TinyML datasets across five critical application domains, selected for 6G relevance, edge compatibility, and validation potential. Experimental results demonstrate practical feasibility: 25.9x compression with <0.5% accuracy loss, and lightweight channel estimation achieving classical-method performance within 453.6 KB memory. Each dataset is characterized for preprocessing complexity, edge deployment feasibility, and alignment with 6G paradigms including integrated sensing and communication (ISAC), non-terrestrial networks (NTN), and mmWave operation. Through this systematic evaluation, we uncover critical gaps including limited support for mmWave and THz bands, indoor-centric bias, and inadequate scaling to high-density scenarios. We provide recommendations for dataset design and open benchmarking to enable reproducible TinyML development for 6G edge intelligence.
