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A data-driven framework for developing a unified density-modulus relationship for the human lumbar vertebral body.

J Mech Behav Biomed Mater

January 2025

Department of Mechanical Engineering, Boston University, Boston, MA 02215, USA; Center for Multiscale and Translational Mechanobiology, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.

Despite the broad agreement that bone stiffness is heavily dependent on the underlying bone density, there is no consensus on a unified relationship that applies to both cancellous and cortical compartments. Bone from the two compartments is generally assessed separately, and few mechanical test data are available for samples from the transitional regions between them. In this study, we present a data-driven framework integrating experimental testing and numerical modeling of the human lumbar vertebra through an energy balance criterion, to develop a unified density-modulus relationship across the entire vertebral body, without the necessity of differentiation between trabecular and cortical regions.

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Despite being studied for almost two centuries, aromaticity has always been a controversial concept. We previously proposed a unified aromatic rule for π-conjugated systems by two-dimensional (2D) superatomic-molecule theory, where benzenoid rings are treated as period 2 2D superatoms (3π-N, 4π-O, 5π-F, 6π-Ne) and, further, bond to form 2D superatomic molecules. Herein, to build a 2D periodic table, we further extend the theory to period 3 (7π-P, 8π-S, 9π-Cl, 10π-Ar) and period 1 (1π-H, 2π-He) elements.

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In this paper, a novel age-structured epidemiological model that simultaneously considers multiple viral strains is proposed. We develop a numerical framework for the study of the dynamics and optimal control by a linearly implicit Euler method, in which the biological meaning is unconditionally preserved. The first order convergence of numerical solutions in a finite time is derived from a uniform numerical boundedness.

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Background: Integrating algorithm-based clinical decision support (CDS) systems poses significant challenges in evaluating their actual clinical value. Such CDS systems are traditionally assessed via controlled but resource-intensive clinical trials.

Objective: This paper presents a review protocol for preimplementation in silico evaluation methods to enable broadened impact analysis under simulated environments before clinical trials.

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Many labels are used within and across subfields to describe personality disorder (PD) and interpersonally-oriented trait dimensions. For example, "interpersonal disorders" is a suggested alternative label to "personality disorders" in clinical research. Other "dark trait" terms, though not proposed as formal labels for PDs, also are used in different research areas for describing externalizing traits.

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