Results 171 to 180 of about 4,856,739 (321)

Stochastic Locomotion Emerging From Body–Environment Interactions in a Mexican Jumping Bean–Inspired Robot

Advanced Intelligent Systems, EarlyView.
Inspired by the Mexican jumping bean, this study presents a centimeter‐scale, electronics‐free robot that merges principles from both the animal and plant kingdoms. A thermo‐responsive actuator mimicking larval motion, enclosed within a uniquely shaped plant‐seed‐inspired shell, generates jumping, rolling, flipping, sliding, and climbing through ...
Ragesh Chellattoan, Alessio Mondini, Edoardo Sinibaldi, Barbara Mazzolai   +3 more
wiley   +1 more source

Bridging the Python Training Gap for Bioscientists in Brazil: Improvements and Challenges. [PDF]

Biochem Mol Biol Educ
Crestana GS, Batista UDS, Funnicelli MIG, Braga LG, Zuvanov L, Bizarria R, de Sousa RM, Ferreira PHN, Winck FV, Margarido GRA, de Mello Varani A, Riaño-Pachón DM, Dos Santos RAC.   +12 more
europepmc   +1 more source

LLM‐Based Multimodal Robotic Endoscope Control Framework for Enhancing Human–Robot Interaction in Minimally Invasive Surgery

Advanced Intelligent Systems, EarlyView.
An large language model‐powered multimodal framework is developed for robotic endoscope control. It integrates speech recognition and real‐time instrument tracking, achieving 89.47% command accuracy with ~1s latency for natural human–robot interaction in minimally invasive surgery.
Yisen Huang, Wing Yin Ng, Qi Dou, Xixin Wu, Shannon Melissa Chan, Yunhui Liu, Philip Wai Yan Chiu, Zheng Li   +7 more
wiley   +1 more source

igraph 1.0 enables fast and robust network analysis across programming languages. [PDF]

PLoS One
Antonov M, Csárdi G, Horvát S, Müller K, Nepusz T, Noom D, Salmon M, Traag V, Welles BF, Zanini F.   +9 more
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Ten simple rules for responsible use of AI and LLMs in computational biology. [PDF]

PLoS Comput Biol
Auslander N.
europepmc   +1 more source

Crease‐Encoded Soft Origami Chambers: A Unified Design‐to‐Fabrication Framework for Low‐Pressure Pneumatic Joints

Advanced Intelligent Systems, EarlyView.
Origami turns a single silicone chamber into three different soft fluidic actuators. Crease angles alone decide whether it elongates, bends, or twists, and the fully folded chambers are cast monolithically in one day. Below 15 kPa, they reach 268% axial stretch, 72° bending, and 55° twist—no strain‐limiting layers, no rigid reinforcements, no vacuum ...
Alexia Le Gall, Mattia Franchi de’ Cavalieri, Gastone Ciuti, Arianna Menciassi, Matteo Cianchetti   +4 more
wiley   +1 more source

Multi-modal learning with incomplete data. [PDF]

Nat Commun
López A, Zobolas J, Dumontier T, Aittokallio T.   +3 more
europepmc   +1 more source

Objectives and Key Results–Driven Multiagent Framework for Mechanical Design and Simulation

Advanced Intelligent Systems, EarlyView.
Objectives and key results (OKR)‐agent, an OKR‐driven multiagent framework, turns a plain‐language engineering goal into completed mechanical simulations. Three peer agents—supervisor, modeler, and simulator—share a compact board of OKR and coordinate external molecular dynamics (MD) and finite‐element solvers through a standardized tool interface. The
Jie Tian, Lin Pang, Jixin Hou, Xiao Sun, James Jaraczewski, Xianyan Chen, Kenan Song, Xiaoming Zhai, Tianming Liu, Keke Tang, Xianqiao Wang   +10 more
wiley   +1 more source

Multi‐Stage Social Value Orientation‐Based Lane‐Changing Driving for Autonomous Vehicles

Advanced Intelligent Systems, EarlyView.
A multi‐stage SVO framework is developed to dynamically infer the social preferences of surrounding vehicles from human driving data. By combining offline learning, online SVO estimation, temporal intention tracking, and interaction‐aware planning, the framework enables autonomous vehicles to adapt lane‐changing decisions and trajectories to evolving ...
Nongrui Qin, Lei Cai, Yilang Luo, Ming Yue, Hsin Guan   +4 more
wiley   +1 more source