Purpose: In the case of Hungarian folk dancers, it is crucial to maintain correct posture and promptly respond to imbalances. However, traditional dances often lack specific training to develop these skills.
Methods: In this present study, twelve dancers (8 male, 4 female, age: 21.7 ± 3.6 years) and ten non-dancers subjects forming a control group (6 male, 4 female, age: 21.6 ± 2.87 years) participated. During the measurements a 60-second long bipedal balancing test on the balance board was completed two times, and a spinning intervention was inserted in between the two sessions. The balance capabilities of the two groups were assessed through the characterization of motion on an unstable board, and the analysis of subject's center of mass and head movements.
Results: Dancers applied a more sophisticated and resource-intensive strategy to address the balancing task, yielding a better balancing performance in terms of balance board parameters. By preferring a solid stability in the medio-lateral direction, a greater fluctuation in the anterior-posterior direction can be observed (e.g., significantly lower SampEn values). The overall more successful performance is further evidenced by within-subject comparison since significant differences were observed mostly within the control group. Based on the results, the advanced balancing ability of the folk dancer group is more likely to be acquired through years of experience.
Conclusion: The results indicate that additional specialized training could further enhance this ability, encouraging the reliance on poorly memorized corrective movements and reducing the risk of injury.
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http://dx.doi.org/10.1186/s13102-024-00850-4 | DOI Listing |
ISA Trans
January 2025
Department of Electronics and Telecommunication, C. V. Raman Global University, Bhubaneswar 752054, Odisha, India. Electronic address:
Early and highly accurate detection of rapidly damaging deadly disease like Acute Lymphoblastic Leukemia (ALL) is essential for providing appropriate treatment to save valuable lives. Recent development in deep learning, particularly transfer learning, is gaining a preferred trend of research in medical image processing because of their admirable performance, even with small datasets. It inspires us to develop a novel deep learning-based leukemia detection system in which an efficient and lightweight MobileNetV2 is used in conjunction with ShuffleNet to boost discrimination ability and enhance the receptive field via convolution layer succession.
View Article and Find Full Text PDFInt Dent J
January 2025
Department of Microbiology, University of Dhaka, Dhaka, Dhaka, Bangladesh.
Hydroxyapatite nanoparticles (HANPs) are becoming increasingly crucial in dental implant applications as they are highly compatible with biological systems, actively support biological processes, and closely resemble bone minerals. This review covers the latest progress in how HANPs are made, studied, and used in dentistry. It looks at critical methods for creating HANPs, such as sol-gel, microwave hydrothermal synthesis, and biomimetic approaches, and how they affect the particles' size, structure, and activity.
View Article and Find Full Text PDFAnn Epidemiol
January 2025
Department of Orthopaedic Surgery, Thompson Laboratory for Regenerative Orthopaedics, School of Medicine, University of Missouri, 1100 Virginia Avenue, Columbia MO, 65211, USA. Electronic address:
Purpose: The objective of this study is to investigate the predictive ability of machine learning models for imbalanced outcomes from national survey data without the use of sampling weights.
Methods: We evaluated the predictive performance of machine learning models on imbalanced outcomes from the US National Health and Nutrition Examination Survey (USNHANES) without using sampling weights. Four machine learning models (support vector machine, random forest, least absolute shrinkage and selection operator regression, and deep neural network) were compared with a logistic model that incorporates the survey's complex sampling design.
Acta Biomater
January 2025
Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA. Electronic address:
Hydrogels composed of collagen, the most abundant protein in the human body, are widely used as scaffolds for tissue engineering due to their ability to support cellular activity. However, collagen hydrogels with encapsulated cells often experience bulk contraction due to cell-generated forces, and conventional strategies to mitigate this undesired deformation often compromise either the fibrillar microstructure or cytocompatibility of the collagen. To support the spreading of encapsulated cells while preserving the structural integrity of the gels, we present an interpenetrating network (IPN) of two distinct collagen networks with different crosslinking mechanisms and microstructures.
View Article and Find Full Text PDFJ Colloid Interface Sci
January 2025
Department of Materials Science and Engineering, Shaanxi Province Key Laboratory of Corrosion and Protection, Xi'an University of Technology, Xi'an 710048 PR China.
Pitting corrosion caused by sulfate-reducing bacteria (SRB) significantly shortens the lifespan of metallic pipelines. Antibacterial coatings containing S-responsive drug-loaded nanocontainers represent a promising method to mitigate SRB corrosion. However, the challenge of balancing rapid bactericide release with continuous antibacterial effect limits their practical application.
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