Results 121 to 130 of about 732,139 (286)
Stochastic control system parameter identifiability [PDF]
The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered.
Herget, C. J., Lee, C. H.
core +1 more source
Toward Constrained Animal Pose Estimation
Quantifying animal behavior is a crucial aspect of the ongoing neuroscientific endeavor to understand the brain, since it is a prerequisite for studying how neural computations relate to behavioral outputs. One method for obtaining an objective yet detailed description of an animal's unconstrained and therefore natural behavior is given by estimating ...
Monsees, A. ; https://orcid.org/0000-0002-1292-365X +1 more
openaire +1 more source
A sequence‐encoded supramolecular construct containing two accessible toeholds is developed herein for enabling multiple editing operations. By introducing specific input strands, it is possible to selectively erase or rewrite digital content through parallel or series toehold‐mediated strand displacement (PTMSD or STMSD).
Jakub Ossowski +3 more
wiley +1 more source
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker +5 more
wiley +1 more source
A memory constrained bayesian optimization via robust online memory estimation
Bayesian optimization (BO) is a memory-intensive algorithm that requires training and evaluating an expensive objective function. In contrast to previous works that use an offline memory estimation to make BO memory-efficient, we propose a robust and ...
Befekadu Bekuretsion +2 more
doaj +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
DNA strands are employed both as dynamic linkers and nanoscale templates for the integration of Ag2S nanoparticles on MoS2, which in turn imparted photothermal responsiveness; this feature permits the selective cargo (fluorophore, quantum dots or an enzyme) release from the MoS2 surface in response to local heat induced by light irradiation.
Kai Chen +3 more
wiley +1 more source
Liquid crystalline inverted lipid phases and reverse micelles are self‐assembled lipid nanostructures that enhance the solubility, stability, and delivery of diverse therapeutics. This review integrates their physicochemical principles, formulation strategies, drug loading mechanisms, and biomedical applications, highlighting their growing ...
Numan Eczacioglu +3 more
wiley +1 more source
Order-Constrained Estimation of Nominal Response Model Parameters to Assess the Empirical Order of Categories. [PDF]
García-Pérez MA.
europepmc +1 more source

