Results 191 to 200 of about 1,734,839 (338)

Fronto-temporal white matter connectivity predicts reversal learning errors [PDF]

, 2015
Kylie H. Alm, Tyler Rolheiser, Feroze B. Mohamed, Ingrid R. Olson   +3 more
openalex   +1 more source

From In‐Silico Optimized Microfabrication to Experimental Validation: Engineering a Tridimensional Epi‐Intraneural Interface

Advanced Functional Materials, EarlyView.
An epi‐intraneural interface is developed through in silico optimization and a novel tridimensional microfabrication pipeline. The device integrates penetrating and epineural contacts on a flexible substrate. Mechanical, electrochemical, and in vivo testing in rat and pig reveal robust implantation, low‐threshold activation, and site‐dependent ...
Federico Ciotti, Andrea Cimolato, Noemi Gozzi, Pietro Palopoli, Luca Brugnoli, Natalija Katic Secerovic, Rebecca Gallivan, Alexander Shokurov, Carlo Menon, Johannes Weichart, Ignacio Delgado‐Martinez, Weiguo Song, Stavros Zanos, Xavier Navarro, Stanisa Raspopovic   +14 more
wiley   +1 more source

Recomposable Layered Metasurfaces for Wavelength‐Multiplexed Optical Encryption via Modular Diffractive Deep Neural Networks

Advanced Functional Materials, EarlyView.
Modular diffractive deep neural network metasurfaces encode and reconstruct holograms across layer combinations and wavelengths, enabling secure, multifunctional operation. Each layer acts independently yet composes jointly, yielding up to m(2N −1) channels for m wavelengths and N layers.
Cherry Park, Youngsun Jeon, Seokho Lee, Yeseul Kim, Junsuk Rho   +4 more
wiley   +1 more source

[Learning from Errors: Qualitative Analysis of Expert Reports on Malpractice in Family Medicine]. [PDF]

Gesundheitswesen
Förster C, Lorenz G, Wilke M, Eissler M, Joos S, Koch R.   +5 more
europepmc   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Rational Design of Printable Carbon Nanotube Transparent Conductive Films via Data‐Driven and Mechanistic Insights

Advanced Functional Materials, EarlyView.
A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou, Ken‐ichi Nomura, Shun Muroga, Makoto Yoneya, Don N. Futaba, Takeo Yamada, Reiko Azumi, Kenji Hata   +7 more
wiley   +1 more source

Visual perceptual processing errors in children with nonverbal learning disabilities (NVLD)

, 2016
Mary Kay Corlett
openalex   +2 more sources

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Learning From Errors: Curriculum Guide for the Morbidity and Mortality Conference With a Focus on Patient Safety Concepts. [PDF]

MedEdPORTAL, 2016
Garcia C, Goolsarran N.
europepmc   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source