Results 181 to 190 of about 871,082 (254)

Editorial: Social and affective domain in home language development and maintenance research. [PDF]

Front Psychol
Zabrodskaja A, Karpava S, Ringblom N.
europepmc   +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

Children Learn Best From Their Peers: The Crucial Role of Input From Other Children in Language Development. [PDF]

Open Mind (Camb)
Schick J, Stoll S.
europepmc   +1 more source

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Analysis of the impact of parents' electronic screen time habits, young children's screen exposure and parent-child interaction on language development delay in young children. [PDF]

Front Pediatr
Wan X, Kang X, Chen S, Du J, Yan F, Bai Y.   +5 more
europepmc   +1 more source

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Advanced Functional Materials, EarlyView.
In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang, Rohan Dhall, Matthew M. Schneider, Cun Li, Chengyu Song, Sundar Kunwar, Hongyi Dou, Natanii R. Yazzie, Henry Tran, Daniel Appuing, Jim Ciston, Nicholas G. Cucciniello, Pinku Roy, Michael T. Pettes, John Watt, Winson Kuo, Haiyan Wang, Ye Cao, Rodney J. McCabe, Aiping Chen   +19 more
wiley   +1 more source

Parental self-efficacy and early language development in deaf and hard-of-hearing children. [PDF]

J Deaf Stud Deaf Educ
Davenport CA, Smolen E, Castellanos I, Dirks E, Houston DM.   +4 more
europepmc   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source