Intelligent stimuli-responsive actuators that can convert environmental energies into mechanical works have garnered significant research interests. Among different actuation principles, Marangoni effect is distinguished due to simplicity, high efficiency, remote manipulation, and water environment adaptability. Nevertheless, both chemical and physical Marangoni actuators face their own challenges with respect to limited chemical loading, precise light illumination, and relatively poor motion controllability. In this study, floating actuators based on graphene oxide foam (GOF), manipulable via dual Marangoni effects and magnetic field, are fabricated by Direct Laser Writing (DLW). This is the first work to realize dual-Marangoni-effect actuators. Specifically, it is observed that the actuator driven by the chemical Marangoni effect can attain an average speed of 0.57 rad s. Meanwhile, the actuator driven by the photothermal Marangoni effect is capable of reaching an average speed of 0.17 rad s, and the average speed is 1.34 cm s under the manipulation of magnetic field. Multi-field coupling and dual Marangoni effects make actuators more flexible and intelligent, with promising potential for intelligent control and biomedical engineering.
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http://dx.doi.org/10.1002/smtd.202401946 | DOI Listing |
Front Rehabil Sci
January 2025
Department of Life Sciences, Health, and Health Professions, Link Campus University, Rome, Italy.
Purpose: The purpose of this case was to investigate objectively and quantitatively the effects of the application of repeated focal muscle vibration (fMV) associated with neurocognitive exercise on a 46-year-old patient with spastic paraparesis secondary to the surgical removal of a C5-C6 ependymoma.
Methods: We have evaluated gait parameters, spasticity, and pain with clinical scales. We have applied focal muscle vibration on quadriceps femoris, hamstrings, gastrocnemius, and iliopsoas muscles bilaterally.
Front Bioeng Biotechnol
January 2025
Department of Physical Education, Tsinghua University, Beijing, China.
Purpose: Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.
View Article and Find Full Text PDFAm J Sports Med
January 2025
Integrative Neuromuscular Sport Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Background: The individual variation in on-snow performance outcomes after anterior cruciate ligament (ACL) reconstruction (ACLR) in elite alpine ski racers has not been reported and may be influenced by specific injury characteristics.
Purpose: To report the performance statistics of elite ski racers before and after ACLR and to identify surgical and athlete-specific factors that may be associated with performance recovery.
Study Design: Descriptive epidemiological study.
Sci Rep
January 2025
Geology and Sustainable Mining Institute (GSMI), Mohammed VI Polytechnic University, Ben Guerir, Morocco.
Accurate statistical modeling of wind speed variability is crucial for assessing wind energy potential, particularly in regions with low wind speeds and significant calm hours. This study evaluates the Champernowne distribution as a novel model for wind speed analysis, comparing its performance with the two-parameter Weibull, three-parameter Weibull, and Rayleigh-Rice distributions. Wind speed data at 10 m hub height over three years (2021-2023) from Ben Guerir, Morocco, were analyzed using statistical metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Bias Error (MBE), Coefficient of Determination (R2), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC).
View Article and Find Full Text PDFJ Neurointerv Surg
January 2025
Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Background: Appropriate management of spontaneous intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) requires rapid, accurate volume estimation. Viz.AI has developed an artificial intelligence (AI)-powered ICH calculation tool that may improve existing methods.
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