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This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Image classification plays a pivotal role in biomedical image analysis. Herein, it is shown that large multimodal models, such as GPT‐4, achieve superior performance in one‐shot learning, generalization, interpretability, and text‐driven image classification. Applications span tissue, cell type, cellular state, and disease classification, outperforming
Wenpin Hou +4 more
wiley +1 more source
In this contribution, it is shown that miniaturized nerve stimulation implants can be used in collaborative networks. Inductive links and ultrasound are combined to supply these implants with energy and data; the advantages and disadvantages of each method, as well as safety risks and possibilities for improvement are discussed and the best ...
Benedikt Szabo +5 more
wiley +1 more source
Health-exploring complexity: an interdisciplinary systems approach HEC 2016: 28 August-2 September 2016, Munich, Germany. [PDF]
Grill E, Müller M, Mansmann U.
europepmc +1 more source
A memristor‐based associative learning circuit is presented for real‐time, fault‐tolerant sensor fusion in autonomous systems. The circuit mimics biological learning to recognize driving scenarios even with missing or degraded sensor inputs. Its low‐power, analog architecture enables robust decision‐making across diverse conditions, offering a ...
Kapil Bhardwaj +3 more
wiley +1 more source
Bachelors in Computer Science Course Descriptions [PDF]
Nova Southeastern University
core +1 more source
A machine learning‐assisted workflow integrates experimental data mining, model training, and SHapley Additive exPlanations‐based interpretation to map the coupled effects of catalyst morphology, particle size, and applied potential on CO2 electroreduction selectivity, revealing critical multifactorial trends for designing Cu‐based catalysts toward ...
Chengxi Yao +6 more
wiley +1 more source
Assessing computational reproducibility in Behavior Research Methods. [PDF]
Ellis DA +12 more
europepmc +1 more source
Exploiting Multitask Deep Learning to Identify Multiple Heavy Metal Contamination at Large Scales
A multitask deep learning framework evaluates manganese, chromium, and cobalt concentrations in European soils, achieving an average R2 of 0.75. From 2009 to 2015, soil concentrations increase significantly. Source analysis identifies anthropogenic manganese and geological chromium and cobalt origins.
Tao Hu +6 more
wiley +1 more source

