Results 221 to 230 of about 459,973 (296)

Real‐Time, Label‐Free Monitoring of Cell Behavior on a Bioelectronic Scaffold

Advanced Functional Materials, EarlyView.
A bioelectronic nanofibrous scaffold is introduced that supports cell growth while enabling real‐time, label‐free monitoring of cellular behavior through impedance measurements. The system correlates electrical signals with cell viability and surface coverage, offering an integrated platform for studying dynamic biological processes and advancing next ...
Dana Cohen‐Gerassi, Offir Loboda, Aakash Jog, Or Messer, Dor Aaron Goldstein, Tomer Reuveni, Moran Aviv, Amit Sitt, Yosi Shacham‐Diamand, Maxim Sokol, Lihi Adler‐Abramovich   +10 more
wiley   +1 more source

Impact of Integrated Control Interventions on Sandfly Populations in Human and Canine Visceral Leishmaniasis Control in Araçatuba, State of São Paulo, Brazil. [PDF]

Insects
Luz-Requena KAM, Suto TMT, Rangel O, Stringheta RCLL, Santos-Doni TR, Rodas LAC, Bresciani KDS.   +6 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

Lightweight Reinforcement Learning for Priority-Aware Spectrum Management in Vehicular IoT Networks. [PDF]

Sensors (Basel)
Iqbal A, Nauman A, Khurshaid T.
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

Identifying core adverse health outcomes for frailty assessment in older adults using administrative data. [PDF]

Front Med (Lausanne)
Silan M, Nicolaio M, Banzato E, Boccuzzo G.   +3 more
europepmc   +1 more source

Hybrid Microdiscs for Magnetically Induced Non‐Cytotoxic Thermal Actuation and Programmable Biomolecule Delivery

Advanced Functional Materials, EarlyView.
Hybrid magnetic microdiscs with customizable size and composition are engineered through refined photolithography and LbL assembly. Embedded Fe3O4 nanoparticles enable localized, non‐cytotoxic heating, while protein cargos can be incorporated in tunable quantities.
Daniela Iglesias‐Rojas, Danny Villanueva, Jon Mentxaka‐Salgado, Nerea Lete, Ane Olazagoitia‐Garmendia, Eduardo Fernández, Iñaki Orue, Alfredo García‐Arribas, Maria Luisa Fdez‐Gubieda, Ainara Castellanos‐Rubio, Robert Morel, Bernard Dieny, Maite Insausti, Idoia Castellanos‐Rubio   +13 more
wiley   +1 more source

A multi-dimensional evaluation model for power enterprise procurement performance based on fuzzy analytic hierarchy process and TOPSIS integration. [PDF]

Sci Rep
Zhao H, Song S, Lv X, Bao Y.
europepmc   +1 more source

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

HAO-AVP: An Entropy-Gini Reinforcement Learning Assisted Hierarchical Void Repair Protocol for Underwater Wireless Sensor Networks. [PDF]

Sensors (Basel)
Hao L, Ma C, Ao J.
europepmc   +1 more source