Non-Target Effects of Beta-Cypermethrin on <i>Baryscapus dioryctriae</i> and Ecological Risk Assessment. [PDF]
Li J +7 more
europepmc +1 more source
Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot
This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley +1 more source
Ecological Risk and Human Health Assessment of Heavy Metals in Sediments of Datong Lake. [PDF]
Li G +6 more
europepmc +1 more source
Context‐Aware Semiautonomous Control for Upper‐Limb Prostheses
A semiautonomous prosthetic control strategy integrates electromyographic‐based intention with computer vision‐driven grasp adaptation and wrist orientation. Comparative experiments with functional tasks evaluate performance, usability, and cognitive workload.
Gianmarco Cirelli +7 more
wiley +1 more source
Spatiotemporal patterns, source apportionment, and ecological risk of major and trace elements in sediment cores from Anzali International Wetland. [PDF]
Pourang N +5 more
europepmc +1 more source
Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context
Agribusiness, EarlyView.
Alexis H. Villacis
wiley +1 more source
We report a biodegradable electrolyte‐gated synaptic phototransistor that combines low‐power UV sensing with memory functionality, offering a sustainable platform for AI vision systems and health‐monitoring technologies. Presented here is a biodegradable, bioinspired synaptic phototransistor (SPT) based on an electrolyte‐gated field‐effect transistor ...
Theodoros Serghiou +5 more
wiley +1 more source
Potential Ecological Risk and Characterization of Floating Microplastics in the Surface Water of a Highly Urbanized Large River in Southeast Asia. [PDF]
Siddique MAM +7 more
europepmc +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source
Characterization, Source Analysis, and Ecological Risk Assessment of Heavy Metal Pollution in Surface Soils from the Central-Western Ali Region on the Tibetan Plateau. [PDF]
Huang Y, He T, Luo J, Ma X, Zhang T.
europepmc +1 more source

