Results 111 to 120 of about 298,347 (266)

siRNA Delivery via Cross‐Linked Gelatin Microparticles Enables Targeted Modulation of Osteogenic‐Vascular Cross‐Talk: An Advanced Human 3D in Vitro Test System for Therapeutic siRNA

Advanced Healthcare Materials, EarlyView.
Osteogenic‐angiogenic cross‐talk is a vital prerequisite for vascularized bone regeneration. In this study, we investigated the effects of siRNA‐mediated silencing of two inhibitory proteins, Chordin and WWP‐1, via CaP‐NP‐loaded gelatin microparticles in osteogenically differentiated microtissues.
Franziska Mitrach, Jonas Kubat, Stefan Simm, Alexandra H. Springwald, Burak Demir, Anton Liebezeit, Michael C. Hacker, Michaela Schulz‐Siegmund   +7 more
wiley   +1 more source

Improving sample efficiency and exploration in upside-down reinforcement learning

Journal of Information and Intelligence
Supervised learning has been demonstrated to be a stable approach for training deep neural networks. Upside-down reinforcement learning solves reinforcement learning problems by using supervised learning, but this method suffers from weak sample ...
Mohammadreza Nakhaei, Reza Askari Moghadam   +1 more
doaj   +1 more source

Evaluation of the Dual Impact of Nanotechnologies on Health and Environment Through Alternative Bridging Models

Advanced Healthcare Materials, EarlyView.
This review explores how alternative invertebrate and small‐vertebrate models advance the evaluation of nanomaterials across medicine and environmental science. By bridging cellular and organismal levels, these models enable integrated assessment of toxicity, biodistribution, and therapeutic performance.
Marie Celine Lefevre, Margherita Bernardeschi, Matteo Battaglini, Gianni Ciofani   +3 more
wiley   +1 more source

Reinforcement learning-based energy management for hybrid electric vehicles: A comprehensive up-to-date review on methods, challenges, and research gaps

Energy and AI
Reinforcement learning is widely used for control applications and has also been successfully implemented for efficient energy management within hybrid electric vehicles.
Mohamed Nadir Boukoberine, Muhammad Fahad Zia, Tarek Berghout, Mohamed Benbouzid   +3 more
doaj   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Text Mining of CVD Synthesis Recipes for 2D Materials

Advanced Materials, EarlyView.
A lightweight, multi‐stage natural language processing framework utilizes fine‐tuned BERT models to extract chemical vapor deposition synthesis knowledge from diverse 2D materials literature. The domain‐adapted workflow integrates classification, named entity recognition, and extractive question answering to systematically retrieve categorical and ...
Ang‐Yu Lu, Richard A. Chen, Aijia Yao, Meng‐Chi Chen, Ji‐Hoon Park, Tianyi Zhang, Xudong Zheng, Nannan Mao, Jiangtao Wang, Zhien Wang, Tomás Palacios, Jing Kong   +11 more
wiley   +1 more source

Kickstarting Deep Reinforcement Learning

, 2018
We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and population based training. Our method places no constraints on the architecture of the teacher or student agents, and it regulates itself to allow the students to surpass their
Schmitt, Simon, Hudson, Jonathan J., Zidek, Augustin, Osindero, Simon, Doersch, Carl, Czarnecki, Wojciech M., Leibo, Joel Z., Kuttler, Heinrich, Zisserman, Andrew, Simonyan, Karen, Eslami, S. M. Ali   +10 more
openaire   +2 more sources

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Deep Successor Reinforcement Learning

, 2016
Learning robust value functions given raw observations and rewards is now possible with model-free and model-based deep reinforcement learning algorithms. There is a third alternative, called Successor Representations (SR), which decomposes the value function into two components -- a reward predictor and a successor map.
Kulkarni, Tejas D., Saeedi, Ardavan, Gautam, Simanta, Gershman, Samuel J.   +3 more
openaire   +2 more sources

Label‐Free SERS Fingerprinting of Neuroprotein Conformational Dynamics in Human Saliva

Advanced Materials, EarlyView.
Galvanic molecular entrapment (GME) is a label‐free method for detecting and quantifying neuroprotein conformational states. This technique enables direct surface binding and in situ hotspot generation around molecules, effectively overcoming challenges related to target localization and mismatched hotspot geometries.
Muhammad Shalahuddin Al Ja'farawy, Jun‐Yeong Yang, Chaewon Mun, Seunghun Lee, Chul Bum Cho, Yoo Hyun Um, Min‐Young Lee, Sung‐Gyu Park, Dong‐Ho Kim, Seung Ho Yang, Ho Sang Jung   +10 more
wiley   +1 more source