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Deep learning combined Monte Carlo simulation reveal the fundamental light propagation in apple puree: Monitoring the quality changes from different cultivar, storage period and heating duration.

Food research international (Ottawa, Ont.)
This work explored the light propagation of purees from a large variability of apple cultivar, storage period and heating duration based on their optical absorption (μ) and reduced scattering (μ') properties at 900-1650 nm, in order to better monitor...

Automatic analysis of high, medium, and low activities of broilers with heat stress operations via image processing and machine learning.

Poultry science
Heat stress is a major welfare problem in the poultry industry, altering broilers' activity levels. Advancements in image processing and machine learning provide opportunities to automatically quantify and analyze broiler activity. This study aimed t...

Biophysical versus machine learning models for predicting rectal and skin temperatures in older adults.

Journal of thermal biology
This study compares the efficacy of machine learning models to traditional biophysical models in predicting rectal (T) and skin (T) temperatures of older adults (≥60 years) during prolonged heat exposure. Five machine learning models were trained on ...

A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.

Journal of thermal biology
The health issues of hazardous operations in high-temperature environments are increasing concerns to the public, especially since global warming and extreme weather conditions have made the high-temperature work more frequent and harsher. The abnorm...

Co-pyrolysis kinetics and enhanced synergy for furfural residues and polyethylene using artificial neural network and fast heating.

Waste management (New York, N.Y.)
The efficient co-utilization of biomass and waste plastics is a key method to address the widely concerned environmental problem and replace traditional energy. Co-pyrolysis behaviors and synergistic effects of furfural residues (FR) and polyethylene...

Developing a seasonal-adjusted machine-learning-based hybrid time‑series model to forecast heatwave warning.

Scientific reports
Heatwaves pose a significant threat to environmental sustainability and public health, particularly in vulnerable regions and rapidly growing cities. They cause water shortages, stress on plants, and an overall drying out of landscapes, reducing plan...

Deep learning-based spatial optimization of green and cool roof implementation for urban heat mitigation.

Journal of environmental management
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...

AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination.

The European physical journal. E, Soft matter
Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qu...

Heat Capacity of Ionic Liquids: Toward Interpretable Chemical Structure-Based Machine Learning Approaches.

Journal of chemical information and modeling
This study focuses on predicting the heat capacity of pure liquid-phase ionic liquids (ILs) using machine learning models from various categories, including support vector machines, instance-based learning, ensemble learning, and neural networks, wit...

How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China.

PloS one
Natural landscapes are crucial resources for enhancing visitor experiences in ecotourism destinations. Previous research indicates that high temperatures may impact tourists' perception of landscapes and emotions. Still, the potential value of natura...