Method-at-a-Glance (MAG) as a Graphical Approach for Method Development in Reversed-Phase Liquid Chromatography of Pharmaceuticals

: Reversed-phase high-performance liquid chromatography (RP-HPLC) remains the dominant separation mode in pharmaceutical and biomedical analysis, yet method development is still largely driven by trial-and-error practices, fragmented literature knowledge, or data-intensive chemometric tools. Despite decades of accumulated chromatographic experience, this knowledge is rarely transferred in a form that enables rapid, rational, and reproducible decision-making at the early stages of method development. This Perspective introduces Method-at-a-Glance (MAG), a conceptual, literature-encoded graphical framework that reimagines RP-HPLC method development as a visually guided process grounded in collective chromatographic knowledge. By abstracting and mapping reported ch romatographic conditions for structurally related pharmaceutical classes, MAG enables the rapid identification of rational starting conditions, significantly reducing the scope of preliminary experimentation. Rather than proposing a new analytical method, this Perspective synthesizes the existing literature into a transferable visual intelligence tool and discusses its implications for accelerating method development, improving reproducibility, and reducing experimental burden. The broader opportunities of MAG are explored, including its potential role in AI-assisted chromatography and sustainability-oriented analytical design. MAG exemplifies how analytical chemistry can move beyond the isolated method reporting tow

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A Solution to Optimal Consensus of Multi-Agent Systems

This paper aims to solve the optimal consensus problem for homogeneous systems of general linear dynamics and a cost function. Specifically, we present a new method rooted in LQ optimal control theory and observer design. This method is fundamentally different from the existing consensus control algorithms, which rely on nonzero eigenvalues of the communication topology to determine the distributed controller. The analytical solution for the distributed controller is derived via Riccati equations and observers, which is parallel to the classical optimal control theory. Theoretical analysis and a simulation example demonstrate that the proposed optimal consensus method achieves significantly faster convergence than conventional approaches. Notably, this framework can be extended to tackle consensus problems in heterogeneous multi-agent systems. 1 | Introduction The distributed cooperative control problem for multi-agent systems has recently garnered significant attention from various scientific communities. Through communication topologies, multiple agents can coordinate to solve tasks that are infeasible for a single agent, with applications spanning distributed robotics, unmanned aerial vehicles, wireless sensor networks, and satellite formation [1–4]. In this context, achieving consensus is a fundamental problem, requiring the design of distributed control protocols that guide all agents to agree on specific variables [5, 6]. As a result, numerous researchers have

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M inimally invasive spine surgery (MISS) has trans- formed the fi eld of spinal surgery, offering reduced tissue disruption, faster recovery, and shorter hospital stays compared with traditional open approaches. 1 En- doscopic spine surgery represents an advancement in minimally invasive techniques, using an endoscope through tiny ports rather than traditional tubular re- tractors to access the spine. 2 – 4 To address the challenges encountered in the 1990s with maintaining surgical visu- alization and instrument manipulation through a single port, biportal endoscopic spine surgery (BESS) was de- veloped, incorporating two separate working portals to

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