Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Investigating the relationship between temporomandibular disorders and personality traits. [PDF]
J Oral Facial Pain HeadacheMarchesi A, Buttironi R, Sardella A.
europepmc +1 more source
Advanced Functional Materials, EarlyView.Integrating polyethyleneimine and carbon black into polyurethane enhances electron transport and mechanical durability. The resulting sensor achieves significantly improved electrical signal and sensitivity, enabling efficient machine learning‐based tactile signal recognition in bionic applications.
Xiangkun Bo +4 more
wiley +1 more source
Intensity of personality traits versus sporting level of historical fencers, streetball players and modern dancers. [PDF]
BMC Sports Sci Med RehabilPiepiora PA +3 more
europepmc +1 more source
Tailoring the Properties of Functional Materials With N‐Oxides
Advanced Functional Materials, EarlyView.The properties of materials bearing N‐oxide groups are often dominated by the polar N+─O− bond. It provides hydrophilicity, selective ion‐binding, electric conductivity, or antifouling properties. Many of the underlying mechanisms have only recently been discovered, and the interest in N‐oxide materials is rapidly growing.
Timo Friedrich +5 more
wiley +1 more source
The personality factor in premium IOLs selection: quantifying Myers-Briggs personality types influence among cataract surgeons. [PDF]
Front Med (Lausanne)Wen Y +9 more
europepmc +1 more source
Two‐Dimensional Materials as a Multiproperty Sensing Platform
Advanced Functional Materials, EarlyView.Various sensing modalities enabled and/or enhanced by two‐dimensional (2D) materials are reviewed. The domains considered for sensing include: 1) optoelectronics, 2) quantum defects, 3) scanning probe microscopy, 4) nanomechanics, and 5) bio‐ and chemosensing.
Dipankar Jana +11 more
wiley +1 more source
Key personality and training factors influencing athletes' mental health - based on machine learning. [PDF]
PLoS OneSun G, Wang J, Zhang S.
europepmc +1 more source
Microsphere Autolithography—A Scalable Approach for Arbitrary Patterning of Dielectric Spheres
Advanced Functional Materials, EarlyView.MicroSphere Autolithography (µSAL) enables scalable fabrication of patchy particles with customizable surface motifs. Focusing light through dielectric microspheres creates well defined, tunable patches via a conformal poly(dopamine) photoresist. Nearly arbitrary surface patterns can be achieved, with the resolution set by the index contrast between ...
Elliott D. Kunkel +3 more
wiley +1 more source