23 papers · ranked by Valyu relevance
Frantis̆ek Bartos̆, Samuel Pawel, Björn S. Siepe
Simulation studies are widely used to evaluate statistical methods. However, new methods are often introduced and evaluated using data-generating mechanisms (DGMs) devised by the same authors. This coupling creates misaligned incentives, e.g., the need to demonstrate the superiority of new methods, potentially…
Eric T. Lofgren, Kellen Myers, Nina H. Fefferman
Computational simulation provides a powerful toolkit for in silico experimentation. However, while the field has developed best practices for the design and implementation of such models, there remains ambiguity in discussions about how to understand and/or interpret their results due to their inherent ability to…
Oluwakemi Tomobi, Sarah DeFazio, Dena Lin, Alyssa Brashear + 4 more
Our study underwent West Virginia University’s IRB review through the WV STEPS Simulation Center and was approved with study Protocol # 2308828386. Written informed consent was obtained from participants on the day of the simulation, prior to participation. Confidentiality was maintained, and data were de-identified…
Soffien Chadli Ajmi, Thomas Bailey Tysland, Bastian Volbers
Background and Objectives Simulation-based interventions serve several purposes in acute stroke care. The diversity of reported objectives, techniques, and outcomes makes it difficult to assess effectiveness and derive guideline recommendations. This scoping review aims to map existing research to identify knowledge…
Luciene Muniz Braga, Pedro Paulo do Prado-Junior, Andréia Guerra Siman, Talita Prado Simão Miranda + 40 more
Background/Objectives: Healthcare-associated infections (HAIs) require specific skills in nursing education, yet their curricular integration often remains fragmented, limiting the consolidation of knowledge and safe clinical practice. This study aimed to explore the perceptions of nursing students from Brazil and Peru…
Yuxuan Li, Kyzyl Monteiro, Hirokazu Shirado, Sauvik Das
Policymakers in domains such as emergency management, public health, and urban planning must make decisions under deep uncertainty, where outcomes depend on how large populations interpret information, coordinate, and adopt over time. Existing tools only partially support this process: tabletop exercises enable…
Kristine Haddeland, Hanne Synøve Briseid, Hege Kristin Aslaksen Kaldheim, Hege Mari Johnsen
Background Simulation exercises are increasingly being used in undergraduate nursing education. The aim of this study was to identify, describe and discuss the factors that facilitate the successful implementation of simulation exercises for the transition to clinical practice in primary healthcare settings experienced…
Jeff Bale, James Day, J. Ives, D. A. Bonn
In a first-year physics inquiry lab, pairs of students were randomly assigned to study pendulum motion using either a physical apparatus or a computer simulation. The experiment required detecting a ~1% difference in period between pendulums released at 10$^\circ$ and 20$^\circ$. This is the subtle failure of the small…
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We present DAISY, a web-based computational tool for the simulation of dynamic magnetic properties of single molecule magnets and supermagnetic nanoparticles. The tool is parametric and accepts relaxation parameters of different mechanisms, including Orbach, Raman, Quantum Tunneling of the Magnetization and the direct…
Erica Cau, Andrea Failla, Valentina Pansanella, Giulio Rossetti
This book chapter covers the evolution of social simulation from classical agent-based models, in which agents interact according to explicitly defined behavioral rules, to AI-enhanced simulations based on Large Language Models and, ultimately, Social Digital Twins: high-fidelity, data-driven representations of…
Louise Prothero, Naim Abdulmohdi, Siân Shaw, Mary Edmonds + 1 more
4.1### Summary of Results This is the first systematic review that meta-analyses results from studies comparing simulation-based education to patient-based clinical teaching in undergraduate nurses, using objectively assessed outcomes. The 42 included studies provide evidence that simulation-based education may be used…
Ling Long, Qiyue Wang, Qianli Yang, Le Chang
Humans can flexibly predict physical events by internally simulating object dynamics in the brain—a capacity lacking in current AI systems. Using a ball collision paradigm with visual occlusion combined with multimodal neuroimaging (fMRI/MEG), we uncover a spatiotemporally organized neural architecture for physical…
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Using the CHARMM36 lipid force field, this investigation employs atomistic molecular dynamics simulation to examine how variations in phosphatidylcholine (PC) lipid composition in murine splenic cancer cells affect membrane properties. While cancer-related alterations in membrane lipid composition are well-established…
Riccardo Tarantino, Salvatore Contino, Livia Gugliotta, Giuseppe Indelicato + 3 more
Actin polymerization is a critical cellular process involved in a wide range of activities, from cell motility to cytokinesis. The complex behavior of this molecular system, resulting in three different phases (i.e., nucleation, elongation, and steady state) is clear by looking at the way these dynamics emerge from a…
V S Krishna Iyer, Komal Bhattacharyya, Raffaele Mendozza, Peter Sollich + 2 more
Computational modeling has emerged as a powerful approach to studying cytoskeletal dynamics. The simulation software Cytosim provides intuitive yet flexible simulations of filament polymerization, cross-linking, and motor activity. Here, we present Cytocalc, a lightweight Python toolkit designed to streamline and…
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Neural network potentials (NNPs) can provide insight into biological processes at atomic resolution. Training these NNPs requires large and diverse datasets of molecules, conformations, and configurations. However, so far little attention has been paid to the description of solvation, despite its importance for…
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Chitosan, a polysaccharide produced via deacetylation of chitin, is widely used in biomedicine, food packaging, and environmental remediation due to its biocompatibility, antimicrobial properties, and tunable solubility. The deacetylation process is generally incomplete and produces random distributions of acetylated…
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Atomistic simulations provide essential mechanistic insights into chemical processes, yet many important phenomena in chemistry and materials science occur on timescales that are inaccessible to molecular dynamics. Existing computational approaches force a choice between atomic resolution on relatively short timescales…
Ana C. C. de Sousa, Alexandre B. Peres, Josep M. Font-Llagunes, Roberto de S. Baptista + 1 more
Cycling is commonly employed in sports performance, rehabilitation, and clinical contexts, while musculoskeletal (MSK) simulations enable the investigation of internal biomechanics that cannot be measured experimentally. Despite growing use, the application, validation, and standardisation of MSK simulations in cycling…
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Embedding mechanophores into polymer matrices to activate mechanochemical reactions has been extensively employed to realize diverse functional applications. Spiropyran (SP) is a widely used mechanophore that undergoes force-induced isomerization into its activated merocyanine (MC) form, accompanied by a color change.…
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Asymmetric catalysts exert control over the reactivity and enantioselectivity of chemical reactions, often through their large size and highly flexible geometries. Current quantum chemical calculations provide a powerful means to predict enantioselectivity through exhaustive conformational sampling at the…
Ben Kawam, Richard McElreath, Julia Ostner, Daniel Redhead + 1 more
Behavioural ecologists aim to understand the causes of animal social structure. Connecting theoretical models of social structure with empirical observations remains, however, a for-midable challenge. While most of the current statistical methods for animal social network analysis rely on data that are aggregated over…
Hélène Grandchamp des Raux, Tommaso Ghilardi, Elisa Raffaella Ferrè, Ori Ossmy
A critical aspect of human cognition is the ability to use our knowledge about the laws of physics to make predictions about physical events. Whether this ability is based on abstract processes or is grounded in our body-environment interactions remains an open debate. We used physical reasoning under altered gravity…