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1.
Scand J Med Sci Sports ; 34(1): e14499, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-37732821

RESUMEN

Studies have shown that neural responses following concentric (CON) and eccentric (ECC) muscle contractions are different, which suggests differences in motor control associated with CON and ECC contractions. This study aims to determine brain activation of the left primary motor cortex (M1) and left and right dorsolateral prefrontal cortices (DLPFCs) during ECC and CON of the right bicep brachii (BB) muscle at low- and high-contraction intensities. Eighteen young adults (13M/5F, 21-35 years) were recruited to participate in one familiarization and two testing sessions in a randomized crossover design. During each testing session, participants performed either ECC or CON contractions of the BB (3 sets × 8 reps) at low- (25% of maximum ECC/CON, 45°/s) and high-intensity (75% of maximum ECC/CON, 45°/s) on an isokinetic dynamometer. Eleven-channel functional near-infrared spectroscopy was used to measure changes in oxyhemoglobin (O2 Hb) from the left M1, and left and right DLPFC during ECC and CON contractions. Maximum torque for ECC was higher than CON (43.3 ± 14.1 vs. 46.2 ± 15.7 N m, p = 0.025); however, no differences in O2 Hb were observed between contraction types at low or high intensities in measured brain regions. High-intensity ECC and CON contractions resulted in greater increases in O2 Hb of M1 and bilateral DLPFC compared to low-intensity ECC and CON contractions (p = 0.014). Our findings suggest no differences in O2 Hb responses between contraction types at high and low intensities. High-contraction intensities resulted in greater brain activation of the M1 and bilateral DLPFC, which may have implications for neurorehabilitation to increase central adaptations from exercise.


Asunto(s)
Contracción Muscular , Músculo Esquelético , Adulto , Humanos , Adulto Joven , Brazo , Encéfalo , Estudios Cruzados , Terapia por Ejercicio , Contracción Muscular/fisiología , Músculo Esquelético/fisiología , Masculino , Femenino
2.
Sensors (Basel) ; 23(16)2023 Aug 16.
Artículo en Inglés | MEDLINE | ID: mdl-37631738

RESUMEN

At microwave frequencies, radar cross-section (RCS) measurements are usually performed by placing the target in the far-field region of the antenna. The wavefront of the radiating field from the antenna can be approximated as planar, ensuring that the incident field and the power interact with the target independently of the antenna. However, for electrically large targets, the required distance becomes significant, posing challenges for implementation. Scaled-model RCS measurements offer an alternative solution. RCS measurements at terahertz and optical frequencies typically require a collimated beam as the source, where the intercepted power and RCS become dependent on the excitation. To address this dependency, researchers have proposed modifying the RCS definition to account for the intercepted power and to analytically formulate the scattering problem. However, such modifications require prior knowledge of the target's geometry and material properties, which are often not readily available in practice. This also limits the study to only canonical targets. In this paper, we propose an alternative approach for modelling the intercepted power. The Gaussian beam is decomposed into a number of plane waves travelling to different directions using the theory of plane wave spectrum. The scattering problem is solved using the full-wave method of moment. Through theoretical proofs and numerical examples involving spheres and a non-canonical target, with a scaled-model aircraft, we demonstrate that the original RCS definition can serve as a good approximation for scaled measurements, provided that the beam waist is approximately four times the target's dimensions. These findings provide valuable guidelines for radar engineers when performing scaled measurements using collimated beams. The results, which match those obtained from full-model measurements, enable us to predict the RCS of full-scale targets. This capability facilitates various target-related applications, such as target characterization, classification, detection, and even recognition.

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