Impact of Dancing on Physical and Mental Health: A Systematic Literature Review

Dance Research, Год журнала: 2024, Номер 42(2), С. 220 - 256

Опубликована: Окт. 29, 2024

Dance, as an expressive art, has increasingly been recognised for its significant impact on physical and mental health. This comprehensive literature review delves into the multifaceted effects of dancing across various populations settings, emphasising implementation in Dance Movement Therapy (DMT) Health (DfH) programmes. Central themes explored include: (1) role dance enhancing neurological cognitive functions through DMT; (2) therapeutic potential health emotional well-being, primarily (3) benefits realised DfH encompassing aspects like cardiovascular health, muscular strength, flexibility, balance, coordination. In this study, forty-eight (48) peer-reviewed studies from prominent databases, spanning period 2020 to 2023 were scrutinised. The analysis reveals extensive applications dance, rehabilitative therapy neurodegenerative disorders a catalyst psychological resilience social integration. Crucially, identifies under-researched areas such long-term therapy, impacts specific demographic groups, integration technology practices. Additionally, findings highlight diverse nature within DMT DfH, underscoring both empirical evidence challenges, including accessibility cultural adaptability. thus acts retrospective examination forward-looking guide, offering insights healthcare professionals, researchers, policymakers complex relationship between overall human

Язык: Английский

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Distinguishing Reality from AI: Approaches for Detecting Synthetic Content

Computers, Год журнала: 2024, Номер 14(1), С. 1 - 1

Опубликована: Дек. 24, 2024

The advancement of artificial intelligence (AI) technologies, including generative pre-trained transformers (GPTs) and models for text, image, audio, video creation, has revolutionized content generation, creating unprecedented opportunities critical challenges. This paper systematically examines the characteristics, methodologies, challenges associated with detecting synthetic across multiple modalities, to safeguard digital authenticity integrity. Key detection approaches reviewed include stylometric analysis, watermarking, pixel prediction techniques, dual-stream networks, machine learning models, blockchain, hybrid approaches, highlighting their strengths limitations, as well accuracy, independent accuracy 80% analysis up 92% using modalities in approaches. effectiveness these techniques is explored diverse contexts, from identifying deepfakes media AI-generated scientific texts. Ethical concerns, such privacy violations, algorithmic bias, false positives, overreliance on automated systems, are also critically discussed. Furthermore, addresses legal regulatory frameworks, intellectual property emerging legislation, emphasizing need robust governance mitigate misuse. Real-world examples systems analyzed provide practical insights into implementation Future directions developing generalizable adaptive fostering collaboration between stakeholders, integrating ethical safeguards. By presenting a comprehensive overview AIGC detection, this aims inform researchers, policymakers, practitioners addressing dual-edged implications AI-driven creation.

Язык: Английский

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Enhancing leaf disease detection accuracy through synergistic integration of deep transfer learning and multimodal techniques

Information Processing in Agriculture, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

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Energy Generation from Plastic Composites: A Systematic Review of Sustainable Practices and Technologies

Circular Economy and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Дек. 4, 2024

Язык: Английский

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