Among the treasures of Chinese art, ethnic dance is an important part. As a key form of expression of national art and emotion, dance has strong regional and gender characteristics for those affected by different ethnic groups and regions. The unique characteristics of the region are the driving force for the masses of all ethnic groups in China to continuously promote the prosperity and development of ethnic and folk dances living alone in different living conditions and living environments. In the analysis of ethnic and folk dances, environmental elements have a profound impact on the rapid development of dance. The main reason for folk dance is the relationship between the costumes of the dance, the connotation of the dance, and the laws of nature, resulting in the derivation of the environment. The article will also focus on a more in-depth discussion and analysis of the characteristics of Chinese folk dance. Scientific research on the regionality of ethnic dance plays a vital role in understanding and inheriting ethnic and folk dances.
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http://dx.doi.org/10.1155/2022/9692803 | DOI Listing |
Cult Med Psychiatry
January 2025
Faculty of General Studies and Advanced Education, Universiti Sultan Zainal Abidin, Kuala Terengganu, Malaysia.
The present study has explored the folk knowledge about the phenomenon of sleep paralysis in Pakistani society. The research aimed to gain a nuanced glimpse focusing on three major factors, culture, religion, and gender, that influence the lived experiences of those who face sleep paralysis. In this qualitative research, to have a holistic perception of indigenous knowledge about it, we selected both male and female participants who have experienced sleep paralysis.
View Article and Find Full Text PDFIntroduction: Gastrointestinal bleeding (GIB) is often encountered among patients with atrial fibrillation (AF) due to the use of anticoagulation. This study assesses disparities in GIB-related mortality among decedents with AF in the United States.
Methods: GIB mortality data in patients with AF from 1999 to 2020 was queried from the CDC database.
NPJ Digit Med
December 2024
Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA.
Where adopted, Autonomous artificial Intelligence (AI) for Diabetic Retinal Disease (DRD) resolves longstanding racial, ethnic, and socioeconomic disparities, but AI adoption bias persists. This preregistered trial determined sensitivity and specificity of a previously FDA authorized AI, improved to compensate for lower contrast and smaller imaged area of a widely adopted, lower cost, handheld fundus camera (RetinaVue700, Baxter Healthcare, Deerfield, IL) to identify DRD in participants with diabetes without known DRD, in primary care. In 626 participants (1252 eyes) 50.
View Article and Find Full Text PDFJ Ethnobiol Ethnomed
November 2024
Instituto Amazónico de Investigaciones Científicas SINCHI, Calle 20 # 5-44, Bogotá, Colombia.
Background: Ethnoichthyology studies the knowledge of human communities about the uses, perception, and behavioral characteristics of fish, based on their cosmology, cosmogony, and culture. This study focused on the Cubeo (Pâmiwâ) ethnic group that inhabits the Cuduyarí River (Vaupés, Colombia) provides information on fishing activities, use of fishes, its ecological distributions (occurrence in rivers, pools, and/or streams) and seasonality (occurrence in low and/or high waters). Additionally, names in the Central Tukano language (Cubeo) are provided.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Key Laboratory of Acoustic Visual Technology and Intelligent Control System, Ministry of Culture and Tourism, Communication University of China, Beijing 100024, China.
Compared with discrete emotion space, image emotion analysis based on dimensional emotion space can more accurately represent fine-grained emotion. Meanwhile, this high-precision representation of emotion requires dimensional emotion prediction methods to sense and capture emotional information in images as accurately and richly as possible. However, the existing methods mainly focus on emotion recognition by extracting the emotional regions where salient objects are located while ignoring the joint influence of objects and background on emotion.
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