The 2021 Richard Skalak Award and the 2021 Editors' Choice Papers
Notice bibliographique
Résumé
Each year, the associate editors of the ASME Journal of Biomechanical Engineering identify the most meritorious papers published in the Journal in the previous calendar year. An external committee then selects the best paper of the year from this list of Editors' Choice papers. The authors of this paper are the recipients of the Richard Skalak Award, named after an early leader within the ASME Bioengineering community. Richard Skalak (1923–1997), who played a leadership role in the formative decades of the discipline of biomedical engineering through his technical contributions in biomechanics, his educational influence on students, and his service to many developing societies and journals. Richard Skalak believed in several central approaches to bioengineering and several central values in working with people. In bioengineering, these were: (1) the useful combination of mathematical and computational modeling with experimental results, to better inform the new biological understanding that is derived, and (2) the inclusion of both microscale and macroscale phenomena in understanding complex biological systems. In terms of mentoring students and collaborating with colleagues, these were: (1) share ideas freely, (2) listen to ideas of others and integrate the best into new developments, and (3) show tolerance and respect for others at all times. These tenets help to guide us as a community and as a journal, and we are honored by the opportunity to contribute to Richard Skalak's legacy by giving an award bearing his name.The Editors thank the 2021 Skalak Award committee: Liesbet Geris (chair), Harry van Lenthe, Joel Boerckel, Michelle Oyen, Claire Villette, and Himanshu Kaul. Congratulations to the authors of the Skalak Award winner and to the authors of the Editors' Choice papers.Eleftheria Michalaki, Zhanna Nepiyushchikh, Josephine M. Rudd, Fabrice C. Bernard, Anish Mukherjee, Jay M. McKinney, Thanh N. Doan, Nick J. Willett, J. Brandon Dixon, “Effect of Human Synovial Fluid From Osteoarthritis Patients and Healthy Individuals on Lymphatic Contractile Activity,” J Biomech Eng. July 2022; 144(7): 071012. doi: 10.1115/1.4053749Brandon Zimmerman, Steve A. Mass, Jeffrey Weiss, Gerard Ateshian, “A Finite Element Algorithm for Large Deformation Biphasic Frictional Contact between Porous-Permeable Hydrated Soft Tissues,” J Biomech Eng. February 2022; 144(2): 021008. doi: 10.1115/1.4052114Rayanne Pinto Costa, Blaise Simplice Talla Nwotchouang, Junyao Yao, Dipankar Biswas, David Casey, Ruel McKenzie, David A. Steinman, Francis Loth, “Transition to Turbulence Downstream of a Stenosis for Whole Book and a Newtonian Analog under Steady Flow Conditions,” J Biomech Eng. March 2022; 144(3): 031008. doi: 10.1115/1.4052370Eleftheria Michalaki, Zhanna Nepiyushchikh, Josephine M. Rudd, Fabrice C. Bernard, Anish Mukherjee, Jay M. McKinney, Thanh N. Doan, Nick J. Willett, J. Brandon Dixon, “Effect of Human Synovial Fluid From Osteoarthritis Patients and Healthy Individuals on Lymphatic Contractile Activity,” J Biomech Eng. July 2022; 144(7): 071012. doi: 10.1115/1.4053749Rawal Atul, Kristen Rhinehardt, Ram Mohan, Max Pendse, “Influence of Hydroxyproline on Mechanical Behavior of Collagen Mimetic Proteins Under Fraying Deformation-Molecular Dynamics Investigations,” J Biomech Eng. August 2021; 143(8): 081009. doi: 10.1115/1.4050648Jordan V. Inacio, Peter Schwarzenberg, Richard Yoon, Andrew Kantzos, Ajith Malige, Chinenye Nwachuku, Hannah Dailey, “Boundary Conditions Matter - Impact of Test Setup on Inferred Construct Mechanics in Plated Distal Femur Osteotomies,” J Biomech Eng. August 2022; 144(8): 081009. doi: 10.1115/1.4053875Ge He, Lei Fan, Yucheng Liu, “Mesoscale Simulation-Based Parametric Study of Damage Potential in Brain Tissue Using Hyperelastic and Internal State Variable Models,” J Biomech Eng. July 2022; 144(7): 071005. doi: 10.1115/1.4053205Peter A. Torzilli, Samie M. Allen, “Effect of Articular Surface Compression on Cartilage Extracellular Matrix Deformation,” J Biomech Eng. September 2022; 144(9): 091007. doi: 10.1115/1.4054108Elizabeth Iffrig, Lucas Timmins, Retta El Sayed, W. Robert Taylor, John Oshinski, “Quantification of Sex-based Differences in Abdominal Aortic Wall Shear Stress Using a Methodology based on Magnetic Resonance Phase Contrast Imaging and the Womersley Solution,” J Biomech Eng. September 2022; 144(9): 091011. doi: 10.1115/1.4054236Luke Nigro, Elisa Arch, “Comparison of Existing Methods for Characterizing Bi-Linear Natural Ankle Quasi-Stiffness: Implications for Passive Orthosis Design,” J Biomech Eng. November 2022; 144(11): 114502. doi: 10.1115/1.4054798Jack Callaghan, Jackie Zehr, “Reaction Forces and Flexion–Extension Moments Imposed on Functional Spinal Units With Constrained and Unconstrained In Vitro Testing Systems,” J Biomech Eng. May 2022; 144(5): 054501. doi: 10.1115/1.4053208Duane, Cronin, Michael Bustamante, Jeffrey Barker, Karin Rafaels, Cynthia Bir, “Assessment of Thorax Finite Element Model Response for Behind Armor Blunt Trauma Impact Loading Using an Epidemiological Database,” J Biomech Eng. March 2021; 143(3): 031007. doi: 10.1115/1.4048644
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».