Digital Twin (DT) technology monitors, simulates, optimizes, models, and predicts the behavior of physical entities. Healthcare is a significant domain where a DT can be functional for multiple purposes. However, these diverse uses of DTs need a clear understanding of both general and specific aspects that can affect their adoption and integration. This paper is a meta-review that leads to the development of a conceptual framework designed to support the high-level evaluation of DTs in healthcare. Using the PRISMA methodology, the meta-review synthesizes insights from 20 selected reviews out of 1,075 studies. Based on this comprehensive analysis, we extract the functional, technological, and operational aspects that characterize DTs in healthcare. Additionally, we examine the structural (e.g., hierarchical) relationships among these aspects to address the various complexity scales in digital health. The resulting framework can promote the effective design and implementation of DTs, offering a structured approach for their assessment.

Tropical mathematics is used to establish a correspondence between certain microscopic and macroscopic objects in statistical models. Tropical algebra gives a common framework for macrosystems (subsets) and their elementary constituents (elements) that is well-behaved with respect to composition. This kind of connection is studied with maps that preserve a monoid structure. The approach highlights an underlying order relation that is explored through the concepts of filter and ideal. Particular attention is paid to asymmetry and duality between max- and min-criteria. Physical implementations are presented through simple examples in thermodynamics and non-equilibrium physics. The phenomenon of ultrametricity, the notion of tropical equilibrium and the role of ground energy in non-equilibrium models are discussed. Tropical symmetry, i.e. idempotence, is investigated.

We provide a combinatorial setting to explore the information content associated with the fulfillment of the Kadomtsev-Petviashvili (KP) II equation. We start from a special family of solutions of KP II, namely, tau-functions of Wronskian type. A solution in this class can be expressed as a sum of exponentials, and we look at combinations of signs (signatures) for the nonvanishing terms in this sum. We prove a characterization of the signatures that return another solution of the KP II equation: they can be represented as choices of signs for columns and rows of a coefficient matrix, so we recover a function satisfying the whole KP hierarchy from this single constraint. The redundancy of this representation for different choices of the initial solution is investigated. Enumerative, information-theoretic, and geometric aspects of this construction are discussed.

Structural equation modeling (SEM) using partial least squares (PLS) has received considerable attention in recent years. We address the increasing fragmentation of PLS-SEM-related research across multiple fields of scientific inquiry by presenting a bibliometric analysis’s results of n = 9,150 documents from the Web of Science database. We identify the main themes by using bibliometric content analysis to explore the PLS-SEM knowledge structure’s definition, its main drivers, and the interplay between the methodology and the application themes over time. Furthermore, we document the dynamics of the PLS-SEM knowledge structure over four periods spanning 1995–2022, unveiling a surge in scientific production and connections among thematic areas due to topic evolution and hybridization. Finally, we investigate the driving forces behind these trends and the relationship between methodology and application themes, providing an integrative view and insights into PLS-SEM research across disciplines.