Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen+4 more
wiley +1 more source
The Effects of Concentrate Supplement Levels on Feed Utilization and Red Meat Production of Blackhead Somali Sheep Fed Natural Pasture Grass Hay as a Basal Diet. [PDF]
Yimenu SA, Letta MU.
europepmc +1 more source
This study, utilizing two large‐cohort datasets, employs interpretable neural networks. It demonstrates that incorporating brain morphology and functional and structural networks enhances predictive accuracy for general psychopathology and its dimensions.
Jing Xia, Nanguang Chen, Anqi Qiu
wiley +1 more source
Effect of Moderate Red Meat Intake Compared With Plant-Based Meat Alternative on Psychological Well-Being: A 10-Wk Cluster Randomized Intervention in Healthy Young Adults. [PDF]
Conner TS+8 more
europepmc +1 more source
Red Meat Consumption Behavior in Elazığ and Consumers’ Opinion in Animal Welfare
İbrahim ŞEKER+4 more
openalex +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni+11 more
wiley +1 more source
Temporal trends in disability adjusted life year and mortality for colorectal cancer attributable to a high red meat diet in China from 1990 to 2021: an analysis of the global burden of disease study 2021. [PDF]
Liu Y, Zhu C, Song H, Che M, Xu B, An B.
europepmc +1 more source
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li+6 more
wiley +1 more source