Protective arm reactions have been shown to be an important injury avoidance mechanism in unavoidable falls. Protective arm reactions have been shown to be modulated with fall height, however it is not clear if they are modulated with impact velocity. The aim of this study was to determine if protective arm reactions are modulated in response to a forward fall with an initially unpredictable impact velocity. Forward falls were evoked via sudden release of a standing pendulum support frame with adjustable counterweight to control fall acceleration and impact velocity. Thirteen younger adults (1 female) participated in this study. Counterweight load explained more than 89% of the variation of impact velocity. Angular velocity at impact decreased (p < 0.001), drop duration increased from 601 ms to 816 ms (p < 0.001), and the maximum vertical ground reaction force decreased from 64%BW to 46%BW (p < 0.001) between the small and large counterweight. Elbow angle at impact (129 degrees extension), triceps (119 ms) and biceps (98 ms) pre-impact time, and co-activation (57%) were not significantly affected by counterweight load (p-values > 0.08). Average triceps and biceps EMG amplitude decreased from 0.26 V/V to 0.19 V/V (p = 0.004) and 0.24 V/V to 0.11 V/V (p = 0.002) with increasing counterweight respectively. Protective arm reactions were modulated with fall velocity by reducing EMG amplitude with decreasing impact velocity. This demonstrates a neuromotor control strategy for managing evolving fall conditions. Future work is needed to further understand how the CNS deals with additional unpredictability (e.g., fall direction, perturbation magnitude, etc.) when deploying protective arm reactions.
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http://dx.doi.org/10.1016/j.jbiomech.2023.111515 | DOI Listing |
Sci Rep
December 2024
College of Civil Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, Inner Mongolia, China.
The mechanical responses of sandy soil under dynamic loading is closely related to protective engineering and geotechnical engineering, is still not fully understood. To investigate the energy attenuation law and propagation velocity of compressed waves in dry sandy soil, this paper focuses on the dynamic response of compression waves in the specimen under single impact and repetitive impact conditions using an improved split Hopkinson pressure bar (SHPB). The results reveal that the length of the specimen follows an exponential relationship with the attenuation of the peak stress.
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December 2024
Civil Engineering Department, Shoolini University, Solan, Himachal Pradesh, 173229, India.
Geopolymer concrete (GPC) offers a sustainable alternative by eliminating the need for cement, thereby reducing carbon dioxide emissions. Using durable concrete helps prevent the corrosion of reinforcing bars and reduces spalling caused by chemical attacks. This study investigates the impact of adding 5, 10, and 15% silica fumes (SF) on the mechanical and durability properties of GPC cured at 60 °C for 24 h.
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December 2024
Arrhythmology, Pacing and Electrophysiology Unit, Cardiology Service, Santa Marta Hospital, Lisbon, Portugal.
Introduction: Low atrial voltage and slow conduction velocity (CV) have been associated with atrial fibrillation (AF); however, their interaction and relative importance as early disease markers remain incompletely understood. We aimed to elucidate the relationship between atrial voltage and CV using high-density electroanatomic (HDE) maps of patients with AF.
Methods: HDE maps obtained during sinus rhythm in 52 patients with AF and five healthy controls were analysed.
Sci Rep
December 2024
School of Mechanical and Electrical Engineering, North University of China, Taiyuan, 030051, Shanxi, China.
Due to the sensitivity of the shaped charge jet to standoff and the complexity of its impact under lateral disturbances, this study aims to investigate the dynamic impact evolution of the jet influenced by standoff and lateral disturbances. A finite element model for the dynamic impact of shaped charge jets was established. Dynamic impact experiments were designed and conducted to validate the effectiveness of the numerical simulations.
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December 2024
Department of Mathematics, University of Gujrat, Gujrat, 50700, Pakistan.
This study is the application of a recurrent neural networks with Bayesian regularization optimizer (RNNs-BRO) to analyze the effect of various physical parameters on fluid velocity, temperature, and mass concentration profiles in the Darcy-Forchheimer flow of propylene glycol mixed with carbon nanotubes model across a stretched cylinder. This model has significant applications in thermal systems such as in heat exchangers, chemical processing, and medical cooling devices. The data-set of the proposed model has been generated with variation of various parameters such as, curvature parameter, inertia coefficient, Hartmann number, porosity parameter, Eckert number, Prandtl number, radiation parameter, activation energy variable, Schmidt number and reaction rate parameter for different scenarios.
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