AIMC Topic: Temperature

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Understanding cellulose pyrolysis via ab initio deep learning potential field.

Bioresource technology Mar 13, 2024
Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available fro...
Molecular Dynamics Simulation Pyrolysis Deep Learning Cellulose Temperature
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Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

International journal of biometeorology Mar 8, 2024
In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded...
Weather Risk Temperature Mexico Dengue Humans Neural Networks, Computer
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Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing.

International journal of biometeorology Mar 5, 2024
The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effec...
Neural Networks, Computer Machine Learning Slovenia Linear Models Humans Thermosensing Temperature Climate Forecasting Wind Humidity
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Artificial Intelligence-Powered Construction of a Microbial Optimal Growth Temperature Database and Its Impact on Enzyme Optimal Temperature Prediction.

The journal of physical chemistry. B Mar 4, 2024
Accurate prediction of enzyme optimal temperature (Topt) is crucial for identifying enzymes suitable for catalytic functions under extreme bioprocessing conditions. The optimal growth temperature (OGT) of microorganisms serves as a key indicator for ...
Temperature Hot Temperature Artificial Intelligence
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Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction.

Bioresource technology Mar 2, 2024
This study developed six machine learning models to predict the biochar properties from the dry torrefaction of lignocellulosic biomass by using biomass characteristics and torrefaction conditions as input variables. After optimization, gradient boos...
Temperature Biomass Machine Learning Charcoal
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Quantitative structure-property relationship modelling on autoignition temperature: evaluation and comparative analysis.

SAR and QSAR in environmental research Feb 19, 2024
The autoignition temperature (AIT) serves as a crucial indicator for assessing the potential hazards associated with a chemical substance. In order to gain deeper insights into model performance and facilitate the establishment of effective methodolo...
Quantitative Structure-Activity Relationship Neural Networks, Computer Temperature Linear Models
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Precision forecasting of spray-dry desulfurization using Gaussian noise data augmentation and k-fold cross-validation optimized neural computing.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Feb 19, 2024
Perceptron models have become integral tools for pattern recognition and classification problems in engineering fields. This study envisioned implementing artificial neural networks to forecast the performance of a mini-spray dryer for desulfurizatio...
Forecasting Neural Networks, Computer Temperature Computer Simulation
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CuO/TiO/MXene-Based Sensor and SMS-TENG Array Integrated Inspection Robots for Self-Powered Ethanol Detection and Alarm at Room Temperature.

ACS sensors Feb 15, 2024
In this study, a high-precision CuO/TiO/MXene ethanol sensor operating at room temperature was prepared. The sensor exhibits excellent response value (95% @1 ppm ethanol), extremely low detection limit (0.3 ppm), fast response/recovery time (16/13 s)...
Robotics Silicones Temperature Transition Elements Ethanol Nitrites
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Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India.

Environmental research Feb 14, 2024
This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Departm...
Hydrology Rain Water Movements Machine Learning Climate Change Environmental Monitoring India Rivers Temperature Models, Theoretical
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Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study.

Journal of environmental management Feb 14, 2024
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management, hydrological processes, and agricultural production. The FAO-56 Penman-Monteith (FAO-56PM) approach is recommended as the standard model...
Neural Networks, Computer Temperature Wind Deep Learning Climate
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