Results 141 to 150 of about 143,911 (316)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Naturally occurring variations in the nod-independent model legume Aeschynomene evenia and relatives: a resource for nodulation genetics

BMC Plant Biology, 2018
Background Among semi-aquatic species of the legume genus Aeschynomene, some have the unique property of being root and stem-nodulated by photosynthetic Bradyrhizobium lacking the nodABC genes necessary for the production of Nod factors.
Clémence Chaintreuil, Xavier Perrier, Guillaume Martin, Joël Fardoux, Gwilym P. Lewis, Laurent Brottier, Ronan Rivallan, Mario Gomez-Pacheco, Mickaël Bourges, Léo Lamy, Béatrice Thibaud, Heriniaina Ramanankierana, Herizo Randriambanona, Hervé Vandrot, Pierre Mournet, Eric Giraud, Jean-François Arrighi   +16 more
doaj   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Fzaero/LSTM-Trajectory-Prediction: LSTM Trajectory Prediction Tool

, 2018
<p>LSTM Trajectory Prediction Tool predicts trajectory of lever upped object from given lever up location. While action is being done, it also analyzes current trajectory up to that point and decides on if action was applied to correct lever up ...
Ahmet Tekden
core   +1 more source

From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku, Sangbin Park, Sunha Hwang, Sunghyun Lim, Won‐Sub Yoon, Jongsoon Kim   +5 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Microbiota diversity of Anopheles gambiae in Bankeng, southern Cameroon, and its association with Plasmodium falciparum infection

mSphere
Malaria control requires the coordination of different strategies due to the lack of an effective vaccine and the emerging resistance of parasites to drugs and of vectors to insecticides.
Maurice Marcel Sandeu, Claudine Grâce Maffo Tatsinkou, Nsa Dada, Franklin Kouhoué Feukam, Flobert Njiokou, Grant L. Hughes, Charles S. Wondji   +6 more
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Gut Microbiota Alterations in Alzheimer’s Disease: Relation with Cognitive Impairment and Mediterranean Lifestyle

Microorganisms
Recently, an association between dysbiosis of the gut microbiota (GMB) and the development of several diseases, such as Alzheimer’s disease (AD), has been proposed.
David Mateo, Nerea Carrión, Cristian Cabrera, Luis Heredia, Montse Marquès, Eva Forcadell-Ferreres, Maria Pino, Josep Zaragoza, Alfons Moral, Lluís Cavallé, José M. González-de-Echávarri, Paloma Vicens, José L. Domingo, Margarita Torrente   +13 more
doaj   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source