Results 161 to 170 of about 8,499 (249)

Corrigendum to "Temporal discounting for self and friends in adolescence: A fMRI study" [Dev. Cogn. Neurosci. 60 (2023) 1-11: 101204]. [PDF]

Dev Cogn Neurosci
van de Groep S, Sweijen SW, de Water E, Crone EA.   +3 more
europepmc   +1 more source

Impact of Packaging and Recycling Systems on Material Recirculation: A Stage‐Decomposition Model

Packaging Technology and Science, EarlyView.
A system‐level view emerges from decomposing recycling into four stages (participation, collection, sorting and process yield), diagnosing constraints and targeting interventions. Cumulative equivalent uses (CEUs) quantify long‐term retention, revealing marginal improvements at high baselines generate disproportionately larger gains than low‐baseline ...
Diogo Figueirinhas, Daniel Hellström, Henrik Pålsson, Yulia Vakulenko   +3 more
wiley   +1 more source

Correction: The role of impulsivity and binge eating in outpatients with overweight or obesity: an EEG temporal discounting study. [PDF]

J Eat Disord
Ferracci S, Manippa V, D'Anselmo A, Bovolon L, Guagnano MT, Brancucci A, Porcelli P, Conti C.   +7 more
europepmc   +1 more source

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño, Alejandro Palacio‐Betancur, Piedad Miranda‐Chiquito, Juan David Amaya, Christian E. Silva, Mariantonieta Gutierrez Soto, Luis Felipe Giraldo   +6 more
wiley   +1 more source

The role of impulsivity and binge eating in outpatients with overweight or obesity: an EEG temporal discounting study. [PDF]

J Eat Disord
Ferracci S, Manippa V, D'Anselmo A, Bovolon L, Guagnano MT, Brancucci A, Porcelli P, Conti C.   +7 more
europepmc   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

Journal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi, Alberto Topini, Alessandro Bucci, Alessandro Ridolfi   +3 more
wiley   +1 more source

Deep Reinforcement Learning Based Autonomous Decision‐Making for Cooperative Uncrewed Aerial Vehicles: A Search and Rescue Real World Application

Journal of Field Robotics, EarlyView.
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling, Maxwell Hogan, Abdulla Tammam, Nabil Aouf   +3 more
wiley   +1 more source

From snapshots to continuous estimates: Augmenting citizen science with computer vision for fish monitoring

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents an end‐to‐end computer‐vision pipeline for monitoring fish migration using underwater video. We integrate field camera deployment, annotation, model training and automated in‐season counting to generate continuous, high‐resolution data on river herring spawning migration.
Zhongqi Chen, Timm Haucke, Sara Beery, Keven Bennett, Austin Powell, Lydia Zuehsow, Robert Vincent, Linda Deegan   +7 more
wiley   +1 more source

Striatal bases of temporal discounting in early adolescents. [PDF]

Neuropsychologia, 2020
Hamilton KR, Smith JF, Gonçalves SF, Nketia JA, Tasheuras ON, Yoon M, Rubia K, Chirles TJ, Lejuez CW, Shackman AJ.   +9 more
europepmc   +1 more source

Path‐Based Deep Reinforcement Learning for On‐Board Routing in Satellite Constellation Networks

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT Efficient usage of available network resources is a crucial factor for broadband services in interconnected satellite constellations. To meet required quality of service standards under heavy network loads, it is essential to optimize traffic distribution among the intersatellite links. To address this challenge, we propose an adaptive traffic
Manuel M. H. Roth, Thomas Jerkovits, Anupama Hegde, Thomas Delamotte, Andreas Knopp   +4 more
wiley   +1 more source