Results 251 to 260 of about 1,099,722 (325)

Domain-generalized person re-identification via refined neuron dropout and reciprocal-expansion re-ranking. [PDF]

Sci Rep
Wang YK, Pan TM, Chen TY.
europepmc   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

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

LoRA-based methods on Unet for transfer learning in aneurysmal subarachnoid hematoma segmentation. [PDF]

BMC Med Imaging
Minoccheri C, Hodgman M, Ma H, Merchant R, Wittrup E, Williamson C, Najarian K.   +6 more
europepmc   +1 more source

DNorm: disease name normalization with pairwise learning to rank. [PDF]

Bioinformatics, 2013
Leaman R, Islamaj Dogan R, Lu Z.
europepmc   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Dynamic adaptive synergistic attention network for visible-infrared person re-identification. [PDF]

Sci Rep
Sha L, Cheng S, Liu S.
europepmc   +1 more source

Using In Situ TEM to Understand the Surfaces of Electrocatalysts at Reaction Conditions: Single‐Atoms to Nanoparticles

Advanced Functional Materials, EarlyView.
This review summarizes recent advances in closed‐cell in situ TEM strategies for accurate determination of the activity and stability of single‐atom catalyst systems during operation. Operando conditions causing dynamic changes of SAC systems are highlighted and we explain why ensemble average‐based optical techniques may benefit from the technological
Martin Ek, Soshan Cheong, Julie Cairney, Richard D. Tilley, Ingemar Persson   +4 more
wiley   +1 more source

Ice Lithography: Recent Progress Opens a New Frontier of Opportunities

Advanced Functional Materials, EarlyView.
This review focuses on recent advancements in ice lithography, including breakthroughs in compatible precursors and substrates, processes and applications, hardware, and digital methods. Moreover, it offers a roadmap to uncover innovation opportunities for ice lithography in fields such as biological, nanoengineering and microsystems, biophysics and ...
Bingdong Chang, Gwendoline A. E. Anand, Rubaiyet Haque, Dylan A. Chiaro, Mona Sharma, Andrew R. Williams, Frank Niklaus, Daryl W. Yee, Gavin M. King, Anpan Han   +9 more
wiley   +1 more source

Ranking-oriented machine learning framework for probabilistic wind power forecasting with temporal reliability constraints. [PDF]

Sci Rep
Li C, Dai J, Tian S, Jiang Y, Hu Q, Chen J, Peng S, Wen Y.   +7 more
europepmc   +1 more source