Physical fitness assessment of a Venezuelan industrial direct labor force population

Interdisciplinary Rehabilitation / Rehabilitacion Interdisciplinaria, Journal Year: 2024, Volume and Issue: 4, P. 88 - 88

Published: April 13, 2024

Introduction: the purpose of this research is to evaluate physical fitness variables Venezuelan workers, considering exercise batteries or submaximal tests that have been little used in industrial environment. Methods: a quantitative, descriptive, cross-sectional, epidemiological and field study was conducted population direct labor workers bipedestation. The sample consisted 185 (M: 136, W: 49) main areas state Aragua-Venezuela. Results: results were obtained on presenting average both sexes. Calculations for obtaining HRmax RAC ml O2 min-1 kg-1 considered. Conclusions: observed, low capacity with values associated age (42,87 M-38,43W), wear tear, poor habits, dietary habits decrease muscle mass

Language: Английский

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Research on the spatial–temporal distribution of three-dimensional carbon footprint in different urban agglomerations in China

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(2)

Published: Jan. 23, 2025

Language: Английский

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How to Forecast Daily Carbon Emissions During Public Health Emergencies: A Novel Self-Attention Multi-Neuron Time Series Model

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102502 - 102502

Published: March 1, 2025

Language: Английский

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Reshaping regional carbon productivity in the Pearl River Delta megaregion: Input-output-based multi-objective optimization to explore low-carbon industrial transitions

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145436 - 145436

Published: April 1, 2025

Language: Английский

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Drivers and Multi-Scenario Projections of Life Cycle Carbon Emissions from China’s Construction Industry

Sustainability, Journal Year: 2025, Volume and Issue: 17(9), P. 3828 - 3828

Published: April 24, 2025

Life cycle carbon emissions from the construction industry (CE) have a profound impact on China’s “dual carbon” goals, with significant posing severe challenges to environment. In this paper, four prediction models were trained and compared, optimal model, Genetic Algorithm Optimized BP Neural Network (GA-BP), was finally selected for multi-scenario of CE. Firstly, study performs comprehensive accounting indicator analysis CE over its entire life cycle. addition, paper further conducts spatial differentiation Subsequently, parameter conducted using an improved STIRPAT followed by LMDI factor decomposition based model. Finally, model performance verified three evaluation metrics: coefficient determination (R2), mean absolute error (MAE), percentage (MAPE). The results indicate that (1) in emission assessment, reached peak 42.52 t per capita annually 8.90 CO2/m2 unit area; (2) year-end resident population has greatest influence CE, other related variables also contributing positively; (3) GA-BP outperforms models, R2 increasing 0.0435 0.0981, MAE reducing 63% 76%, MAPE decreasing 23% 68%.

Language: Английский

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A Statistical Model-Based Study of the Coupled Relationship between Labor Force Skill Complementarity and Economic Growth

Published: Nov. 18, 2024

Language: Английский

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Spatio-temporal characteristics and scenario prediction of carbon emissions from land use in Jiangxi Province, China

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 21, 2024

Language: Английский

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