Results 81 to 90 of about 988,211 (198)

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High BMI: A Secondary Analysis of the IDEA Trial

Arthritis Care &Research, Accepted Article.
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source

Multivariate data analysis: Validation of an instrument for the evaluation of teaching digital competence. [PDF]

F1000Res, 2023
Cisneros-Barahona AS, Marqués-Molías L, Samaniego-Erazo N, Mejía-Granizo C, De la Cruz-Fernández G.   +4 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Capturing fluctuations in multivariate intensive longitudinal data

Methods in Psychology
This paper introduces a novel method for intensive longitudinal data incorporating dimension reduction and time series analyses. The method capitalizes on the notion of determining distance or similarity parameters in the data.
Katerina M. Marcoulides, Hannah Hamling
doaj   +1 more source

A Holistic Platform Approach for Developing Robust Pulmonary mRNA Delivery: Integrating Novel Phenolic Acid‐Derived Ionizable Lipids and Device Engineering

Advanced Functional Materials, EarlyView.
An integrated pulmonary mRNA delivery platform combining novel biodegradable syringic acid‐derived ionizable lipids, design‐of‐experiments formulation optimization, and vibrating‐mesh nebulizer engineering enabled stable aerosolization and efficient lung delivery.
Neha Kaushal, Younan Ma, Asad Khanmohammed, Dipen Parande, Hanming Zhang, Saket Dolare, Juliet Chen, Apiwat Wangweerawong, Saswata Karmakar, Hongfeng Deng, Frank Koppenhagen, Shraddha Sharma, Eric Reyes, Sherry He, Lianne Boeglin, Caroline Woo, Azadeh Paksa, Ayed Allawzi, Anusha Dias, Gregory Troiano, Shrirang Karve, Frank DeRosa   +21 more
wiley   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Resistance to Overdoping Allows Over 2000 S cm−1 Conductivity in P(g3BTTT) With Anion‐Exchange Doping

Advanced Materials, EarlyView.
Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger, Maximilian M. Horn, Eva Röck, Diego Rosas Villalva, Lize Bynens, Jochen Vanderspikken, Christina Kousseff, Silène Gobeil, Olivier Bardagot, Nesibe Akmanşen‐Kalayci, Sarah H. Tolbert, Iain McCulloch, Wouter Maes, Demetra Tsokkou, Natalie Banerji   +14 more
wiley   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

MGIDI: a powerful tool to analyze plant multivariate data. [PDF]

Plant Methods, 2022
Olivoto T, Diel MI, Schmidt D, Lúcio AD.   +3 more
europepmc   +1 more source

Charge Storage and Dark Photocatalysis in Multivariate Ti‐Based Metal‐Organic Frameworks

Advanced Materials, EarlyView.
The mixed‐linker series of the titanium‐based metal–organic framework COK‐47 enables systematic tuning of photoresponsiveness and (dark) photocatalytic activity, deepening our understanding of structure‐property‐function relationships. Tailored metal‐to‐ligand charge transfer between the secondary building units (metal‐oxo layers and organic linkers ...
Julia E. Knapp, Bibhuti Bhusan Rath, Borja Ortín‐Rubio, Lukas Bauder, Kristina Gjorgjevikj, Saunak Das, Mariia Ferree, Frédéric Laquai, Lorenzo Tesi, Bettina Baumgartner, Simon Krause, Bettina V. Lotsch   +11 more
wiley   +1 more source