Results 161 to 170 of about 61,664 (222)

Mechanics of blunting of actin-myosin interaction dynamics by the actinopathy-causing mutation E334Q in cytoskeletal γ-actin. [PDF]

J Physiol
Pertici I, Buonfiglio V, Greve JN, Battirossi E, Fanelli D, Manstein DJ, Bianco P.   +6 more
europepmc   +1 more source

Wireless, Battery‐Free Wearable Pressure Sensor for Compression Therapy Entirely Built on Surface Mount Devices

Advanced Intelligent Systems, EarlyView.
This work presents a flexible, battery‐free sensor that forms a closed‐loop feedback system for smart compression therapy devices. Its scalable surface‐mount manufacturing, compact form factor, and wireless communication enable seamless integration with a wide range of active compression garments, improving user experience and therapeutic outcomes ...
Sinuo Zhao, Hongru Chen, Isaac Seeto, Phuoc Thien Phan, Chi Cong Nguyen, Tran Bach Dang, Kefan Zhu, Michael Listyawan, Minh Cuong Duong, Alice Ma, Thanh Nho Do, Hoang‐Phuong Phan   +11 more
wiley   +1 more source

Pulmonary Metastasis of Anal Squamous Cell Carcinoma Nine Years Following Treatment. [PDF]

Cureus
Madani MS, Deogaonkar A, Naum AS, Gordon R, Borum ML.   +4 more
europepmc   +1 more source

Modeling and Characterization of a Self‐Sensing Soft Hydraulic Muscle

Advanced Intelligent Systems, EarlyView.
This article presents the self‐sensing soft hydraulic muscle (SSHM), a novel soft actuator capable of simultaneously sensing force and length without external sensors. A comprehensive model accurately predicts SSHM behavior, validated experimentally with minimal errors. Using propylene glycol enhances durability and reduces hysteresis.
Nhu An Phan, Phuong Linh Dao, Duc Tu Vu, The Doan Le, Sy Trung Ngo, Minh Tri Phan, T. Thang Vo‐Doan, Ke Wu, Mai Thanh Thai   +8 more
wiley   +1 more source

Research on Shrinkage in Lithium Slag Geopolymer Mortar: Effects of Mix Proportions and a Shrinkage Prediction Model. [PDF]

Materials (Basel)
Wang L, Pan G, Wu C, Xu S, Zhu D.
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Data-driven linearization of dynamical systems. [PDF]

Nonlinear Dyn
Haller G, Kaszás B.
europepmc   +1 more source

Data‐Driven Modeling of Forces Exerted by Pneumatic Actuators for a Pediatric Exosuit

Advanced Intelligent Systems, EarlyView.
This work presents the experimental analysis and data‐driven modeling of the interaction forces between soft pneumatic actuators designed to assist upper‐extremity motion in a pediatric exosuit and an engineered test rig, across different experimental conditions: (A) force profiling of shoulder actuators, with varying actuator anchoring points and ...
Mehrnoosh Ayazi, Ipsita Sahin, Caio Mucchiani, Elena Kokkoni, Konstantinos Karydis   +4 more
wiley   +1 more source

Research on the Stability Model in Discrete Dynamical Systems with the Lorenz Attractor and the Kropotov-Pakhomov Neural Network. [PDF]

Entropy (Basel)
Gospodinova EA.
europepmc   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

Advanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source