In competitions, judokas tend to have a predominant direction of fall: forwards or backwards. A relationship was hypothesized between the direction of fall and certain parameters of the judokas' postural activities. 20 judokas, 16 to 19 yr. old (17.7 +/- 0.4 yr.), had practised judo for at least seven years. They were separated into two groups. The group of forward fallers (n = 9) and the group of backward fallers (n = 11) performed posturokinetic tests to assess their static and dynamic balance. One parameter assessed through the analysis of postural activities, the average position of anteroposterior dynamic oscillations, was inversely related to the judokas' direction of fall. Postural activities might not play a direct role but perhaps an indirect one in the direction of falls by expert judokas.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.2466/pms.101.3.885-890 | DOI Listing |
Sensors (Basel)
January 2025
China Railway Construction Bridge Engineering Bureau Group Co., Ltd., Tianjin 300300, China.
GNSS-RTK offers numerous advantages and broad prospects in structural dynamic monitoring in civil engineering. However, in practical applications, GNSS-RTK accuracy is susceptible to the monitoring environments, causing actual monitoring accuracy to fall below its calibrated accuracy. This study investigates the monitoring accuracy and spectral characteristics of GNSS-RTK based on stability tests under different environments related to reflection and obstruction conditions (i.
View Article and Find Full Text PDFTransl Psychiatry
January 2025
Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
This state-of-the-art review explores the relationship between depression and diabetes, highlighting the two-way influences that make treatment challenging and worsen the outcomes of both conditions. Depression and diabetes often co-occur and share genetic, lifestyle, and psychosocial risk factors. Lifestyle elements such as diet, physical activity, and sleep patterns play a role on the development and management of both conditions, highlighting the need for integrated treatment strategies.
View Article and Find Full Text PDFASN Neuro
January 2025
Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, USA.
In light of the increasing importance for measuring myelin ratios - the ratio of axon-to-fiber (axon + myelin) diameters in myelin internodes - to understand normal physiology, disease states, repair mechanisms and myelin plasticity, there is urgent need to minimize processing and statistical artifacts in current methodologies. Many contemporary studies fall prey to a variety of artifacts, reducing study outcome robustness and slowing development of novel therapeutics. Underlying causes stem from a lack of understanding of the myelin ratio, which has persisted more than a century.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
Institute of AI for Industries, Chinese Academy of Sciences Nanjing, 168, Tianquan Road, Nanjing 211135, China.
In this study, we designed a biomimetic artificial visual system (AVS) inspired by biological visual system that can process RGB images. Our approach begins by mimicking the photoreceptor cone cells to simulate the initial input processing followed by a learnable dendritic neuron model to replicate ganglion cells that integrate outputs from bipolar and horizontal cell simulations. To handle multi-channel integration, we utilize a nonlearnable dendritic neuron model to simulate the lateral geniculate nucleus (LGN), which consolidates outputs across color channels, an essential function in biological multi-channel processing.
View Article and Find Full Text PDFBrain Sci
December 2024
Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL 32816, USA.
Brain connectivity analysis plays a crucial role in unraveling the complex network dynamics of the human brain, providing insights into cognitive functions, behaviors, and neurological disorders. Traditional graph-theoretical methods, while foundational, often fall short in capturing the high-dimensional and dynamic nature of brain connectivity. Graph Neural Networks (GNNs) have recently emerged as a powerful approach for this purpose, with the potential to improve diagnostics, prognostics, and personalized interventions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!