Results 191 to 200 of about 1,053,671 (295)

Step 15 Creation of database [PDF]

, 2017
本村 浩之
core  

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

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

SorghumBase: a knowledgebase for sorghum genomics, phenomics, and stakeholder engagement. [PDF]

Genetics
Gladman N, Olson A, Kumari S, Wei S, Chougule K, Lu Z, Tello-Ruiz MK, Van Buren P, Kumar V, Zhang L, Olson A, Kim C, Braynen J, Hayes C, Xin Z, Klein R, Rooney W, Provart N, Pasha A, O'Meara A, Shakoor N, Michael TP, Harrison M, Ware D.   +23 more
europepmc   +1 more source

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Comparative outcomes of gram-positive and gram-negative intraoperative infections in degenerative scoliosis: a 10-year propensity score-matched analysis. [PDF]

Spine Deform
Ilyas YB, Aguilar TM, Mansour HM, Kurker KP, Adachi K, Sadeh M, Chaudhry NS, Mehta AI.   +7 more
europepmc   +1 more source

Bio‐Inspired Magnetically Tunable Structural Colors from Elliptical Self‐Assembled Block Copolymer Microparticles

Advanced Functional Materials, EarlyView.
Cephalopod‐inspired photonic microparticles with dynamic structural coloration are fabricated via confined self‐assembly of linear block copolymers into ellipsoids containing stacked lamellae. Embedded superparamagnetic nanoparticles enable rapid magnetic alignment, restoring vivid, angle‐dependent color.
Gianluca Mazzotta, Simone Bertucci, Jose Mendoza‐Carreño, Agustín Mihi, Paola Lova, Davide Comoretto, Ullrich Steiner, Marco Lattuada, Andrea Dodero   +8 more
wiley   +1 more source

Arteriovenous fistulas are associated with superior outcomes in very elderly hemodialysis patients: a nationwide cohort study. [PDF]

Korean J Intern Med
Kim HD, Kim DH, Kim H, Lee HS, Yang SB, Shin SJ, Park HS, vascular access working group of the Korean Society of Dialysis Access.   +7 more
europepmc   +1 more source

Additive Manufacturing of NiTi Shape Memory Alloys for Elastocaloric Applications: A Review

Advanced Functional Materials, EarlyView.
Additive manufacturing enables complex NiTi architectures that overcome key limitations in elastocaloric refrigeration, including poor heat transfer and high mechanical work input. This review surveys recent advances in LPBF‐ and DED‐fabricated NiTi shape memory alloys for elastocaloric applications, highlighting process–structure–performance ...
Ignatius Andre Setiawan, Mohammad Mehrali, Jaka Tušek, Shiva Mohajerani, Xiebin Wang, Dermot Brabazon, Mohammad Elahinia, Mehrshad Mehrpouya   +7 more
wiley   +1 more source

ATDD: Multi-lingual dataset for auto-tune detection in music recordings. [PDF]

Data Brief
Gohari M, Bestagini P, Benini S, Adami N.   +3 more
europepmc   +1 more source