Results 101 to 110 of about 418,008 (299)

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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Bayesian analysis of resolved stellar spectra: application to MMT/Hectochelle Observations of the Draco dwarf spheroidal

, 2015
We introduce a Bayesian method for fitting faint, resolved stellar spectra in order to obtain simultaneous estimates of redshift and stellar-atmospheric parameters. We apply the method to thousands of spectra---covering 5160-5280 Angs. at resolution R~20,
Mateo, Mario, Olszewski, Edward W., Walker, Matthew G.   +2 more
core   +2 more sources

Near‐Infrared Organic Photovoltaic Electrodes for Subretinal Neurostimulation

Advanced Functional Materials, EarlyView.
Organic photovoltaic electrodes based on the D18:Y6 blend enable precise and light‐controlled activation of retinal ganglion cells in a degenerating retina. NIR Light‐driven activation of retinal ganglion cells, tunable stimulation parameters, and biocompatibility with human retinal organoids highlight their potential for next‐generation prosthetics ...
Andrea Corna, Katarina Gugujonovic, Manuela Schiek, Alessandro Bellapianta, Paul Werginz, Amelie Ziller, Markus Clark Scharber, Ahmad Salti, Matthias Bolz, Mihai Irimia‐Vladu, Günther Zeck   +10 more
wiley   +1 more source

Optimization method for variable fractional delay filters based on gradient descent

Tongxin xuebao
In order to address the requirements for low distortion transmission of variable fractional delay filters, an optimization method based on gradient descent and root mean square propagation was proposed.
ZHUANG Ling, HAO Hanjie
doaj  

Bridging IoT devices and machine learning for predicting power consumption: case study universitas Widya Dharma Pontianak

Energy Informatics
Multiple methods have been developed and implemented to reduce dependence on fossil fuels and conserve electricity. However, accurately predicting electricity consumption is essential before reducing it.
Genrawan Hoendarto, Ahmad Saikhu, Raden Venantius Hari Ginardi   +2 more
doaj   +1 more source

Evaluating the Reliability and Validity of the Maastricht Clinical Teaching Questionnaire in Bahrain

Oman Medical Journal, 2019
Objectives: The Maastricht Clinical Teaching Questionnaire (MCTQ) was developed to evaluate clinical teachers’ supervisory skills during undergraduate clinical rotations. Evidence exists supporting the reliability and validity of this questionnaire.
Ahmed Al Ansari, Khaled Saeed Tabbara
doaj   +1 more source

Heuristic and exact solutions to the inverse power index problem for small voting bodies [PDF]

, 2012
Power indices are mappings that quantify the influence of the members of a voting body on collective decisions a priori. Their nonlinearity and discontinuity makes it difficult to compute inverse images, i.e., to determine a voting system which induces a
Kurz, Sascha, Napel, Stefan
core   +2 more sources

Investigating the Impact of Data Normalization Methods on Predicting Electricity Consumption in a Building Using different Artificial Neural Network Models. [PDF]

The study investigates the impact of data normalization on the prediction of electricity consumption in buildings using four multilayer Artificial Neural Networks (ANN) algorithms: Long Short-Term Memory Networks (LSTM), Levenberg–Marquardt Back ...
Fu, Nuodi, Kim, Moon Keun, Kim, Yang Seon, Liu, Jiying, Srebric, Jelena, Wang, Junqi   +5 more
core   +1 more source

Peptide Sequencing With Single Acid Resolution Using a Sub‐Nanometer Diameter Pore

Advanced Functional Materials, EarlyView.
To sequence a single molecule of Aβ1−42–sodium dodecyl sulfate (SDS), the aggregate is forced through a sub‐nanopore 0.4 nm in diameter spanning a 4.0 nm thick membrane. The figure is a visual molecular dynamics (VMD) snapshot depicting the translocation of Aβ1−42–SDS through the pore; only the peptide, the SDS, the Na+ (yellow/green) and Cl− (cyan ...
Apurba Paul, Archith Rayabharam, Lisa Almonte, Eveline Rigo, Joshy Joseph, Ashutosh Kumar, Zhuxin Dong, Narayana Aluru, Gregory Timp   +8 more
wiley   +1 more source

An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions

Scientific Reports
This study introduces a novel hybrid model for accurate CO2 emissions prediction, supporting sustainable decision-making. The model integrates the Gaussian mutation and shrink mechanism-based moth flame optimization (GMSMFO) algorithm with an extreme ...
Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa   +1 more
doaj   +1 more source