AIMC Topic: Hot Temperature

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Corrugated paraffin nanocomposite films as large stroke thermal actuators and self-activating thermal interfaces.

ACS applied materials & interfaces
High performance active materials are of rapidly growing interest for applications including soft robotics, microfluidic systems, and morphing composites. In particular, paraffin wax has been used to actuate miniature pumps, solenoid valves, and comp...

Assessment for water quality by artificial neural network in Daya Bay, South China Sea.

Ecotoxicology (London, England)
In this study, artificial neural network such as a self-organizing map (SOM) was used to assess for the effects caused by climate change and human activities on the water quality in Daya Bay, South China Sea. SOM has identified the anthropogenic effe...

Characterize the dynamic changes of volatile compounds during the roasting process of Wuyi rock tea (Shuixian) integrating GC-IMS and GC × GC-O-MS combined with machine learning.

Food chemistry
Understanding aroma compounds' changes during Shuixian roasting is vital for scientific guidance. This study used gas chromatography-ion mobility spectrometry (GC-IMS) and two-dimensional gas chromatography-olfactory-mass spectrometry (GC × GC-O-MS) ...

Artificial neural networks computing for heat transfer flow of hybrid nanofluid in rectangular geometry.

Computers in biology and medicine
This study explores the complex dynamics of heat transfer in hybrid nanofluid flow, focusing on the unsteady squeezing motion of Graphene-FeO/water confined between two parallel plates under the influence of a magnetic field. The lower plate is assum...

Machine learning predicting sintering temperature for ceramsite production from multiple solid wastes.

Waste management (New York, N.Y.)
An efficient machine learning model was developed to accurately predict the sintering temperature of ceramsite synthesized from various solid waste materials. Based on experimental data from 236 samples, eight key chemical components were defined as ...

Approaches for Measuring and Predicting Fouling During Thermal Processing of Dairy Solutions.

Comprehensive reviews in food science and food safety
Fouling during the thermal processing of dairy products remains a significant challenge, reducing operational efficiency, increasing energy consumption, and complicating cleaning cycles. This review critically assesses current methods for measuring a...

Hyperspectral imaging combined with DBO-SVM for the germination prediction of thermally damaged seeds.

Analytical methods : advancing methods and applications
Healthy development of the maize seed industry plays a key role in the effective supply of agricultural products and ensures national food security. Thermal damage to seeds significantly affects crop yield, seed vitality and nutritional value, making...

Quantitative determination of acid value in palm oil during thermal oxidation using Raman spectroscopy combined with deep learning models.

Food chemistry
Accurate monitoring of acid value (AV) is critical for edible oil quality control, yet traditional chemometric methods often face limitations in handling complex spectral data. This study combines Raman spectroscopy with deep learning, including Conv...

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...