Results 181 to 190 of about 556,737 (306)

Distribution characteristics and influencing factors of carbon storage in <i>Populus</i> plantations with different stand ages in the Luxi Yellow River floodplain, China. [PDF]

Front Plant Sci
Wang Z, Sun X, Guo Y, Zhou C, Liang J, Wu H, Huang C, Gao X, Zhang Y.   +8 more
europepmc   +1 more source

Three Synchronized, Miniaturized, Wireless Inertial Measurement Unit Sensors for Automated Gait and Balance Analysis System

Advanced Intelligent Systems, EarlyView.
This study presents a compact, three IMU wearable system that enables accurate motion capture and robust gait‐feature extraction, thereby supporting reliable machine learning‐based balance evaluation. Accurate assessment of balance is critical for fall prevention and targeted rehabilitation, particularly in older adults and individuals with ...
Seok‐Hoon Choi, Ki‐Hoon Kim, Heung Jin Park, Yuna Kim, Hyunjin Lee, Yu Bin Lee, Youn Joung Kang, Sungchul Huh, Min‐Ho Seo   +8 more
wiley   +1 more source

Straightforward model-based approach using only field data and open-source maps to improve carbon stock estimates for REDD + projects. [PDF]

Sci Rep
Haneda LE, de Almeida DRA, Kamimura RA, Gomes SHM, Sanchez AK, de Azevedo BP, de Souza CR, Naves RP, Valle D.   +8 more
europepmc   +1 more source

A Multimodal Laser‐Induced Graphene‐Based Flexible Sensor for Soft Robotic Hand Environmental Perception

Advanced Intelligent Systems, EarlyView.
A multimodal laser‐induced graphene (LIG)‐based flexible sensor is developed to detect proximity and contact signals. Integrated into a soft robotic hand, it enables vision‐free object searching and grasping. Combined with a convolutional neural network, the system achieves accurate material and texture recognition, enhancing the capability of ...
Youning Duo, Jinxi Duan, Xinyu Hao, Kaining Tao, Xin Liu, Mingyuan Li, Xingyu Chen, Wenbo Liu, Zonghao Zuo, Li Wen   +9 more
wiley   +1 more source

Global impacts of transportation infrastructure on forest degradation and loss. [PDF]

Nat Commun
Zhou D, Xiao J, Liu S, Huang L, Zhang L, Fan J, Zhao S.   +6 more
europepmc   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

Advanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi   +8 more
wiley   +1 more source

LiDAR-derived forest inventory data to map and quantify ecologically important large trees across large spatial extents. [PDF]

Ecol Appl
Pitt DG, Venier LA, Adams GW, McCartney AW.   +3 more
europepmc   +1 more source

Myoelectric Origami‐Based Soft Robotic Knee Exoskeleton to Enhance Sit‐to‐Stand Assistance in Elderly Populations

Advanced Intelligent Systems, EarlyView.
This work presents a lightweight Miura‐origami soft knee exoskeleton powered by vacuum actuation and integrated with a multimodal physiological intent‐recognition system, providing real‐time assistance during sit‐to‐stand movement to reduce muscle effort and improve user comfort.
Yuchuan Jia, Xingjian Ye, Xuanyi Zhou, Yong Ling, Daniela Rus, Chen‐Hua Yeow   +5 more
wiley   +1 more source

Forest Degradation and Weather Jointly Affect Early-Life Development in a Tropical Understory Bird. [PDF]

Glob Chang Biol
Kung'u GN, Cousseau L, Canoine V, Heiskanen J, Githiru M, Njoroge P, Pellikka P, Habel JC, Lens L, Apfelbeck B.   +9 more
europepmc   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source