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Temperature

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Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques.

Sensors (Basel, Switzerland)
Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality...

Assessment of Laying Hens' Thermal Comfort Using Sound Technology.

Sensors (Basel, Switzerland)
Heat stress is one of the most important environmental stressors facing poultry production and welfare worldwide. The detrimental effects of heat stress on poultry range from reduced growth and egg production to impaired health. Animal vocalisations ...

A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition)
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...

Fate of pirlimycin and antibiotic resistance genes in dairy manure slurries in response to temperature and pH adjustment.

The Science of the total environment
Quantifying the fate of antibiotics and antibiotic resistance genes (ARGs) in response to physicochemical factors during storage of manure slurries will aid in efforts to reduce the spread of resistance when manure is land-applied. The objectives of ...

Occurrence prediction of pests and diseases in cotton on the basis of weather factors by long short term memory network.

BMC bioinformatics
BACKGROUND: The occurrence of cotton pests and diseases has always been an important factor affecting the total cotton production. Cotton has a great dependence on environmental factors during its growth, especially climate change. In recent years, m...

Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models.

Food research international (Ottawa, Ont.)
In this study, the inhibitory capacity of Lactobacillus sakei strain L115 against Listeria monocytogenes has been assayed at 4, 8, 11, 15 and 20 °C in broth culture. Besides, the use of predictive microbiology models for describing growth of both mic...

Ceftolozane-tazobactam in an elastomeric infusion device for ambulatory care: an in vitro stability study.

European journal of hospital pharmacy : science and practice
OBJECTIVES: Published in vitro stability data for ceftolozane-tazobactam supports intermittent short duration infusions. This method of delivery is not feasible for many outpatient antimicrobial therapy services that provide only one or two visits pe...

Predicting the higher heating value of syngas pyrolyzed from sewage sludge using an artificial neural network.

Environmental science and pollution research international
Sludge pyrolysis is a complex process including complicated reaction chemistry, phase transition, and transportation phenomena. To better evaluate the use of syngas, the monitoring and prediction of a higher heating value (HHV) is necessary. This stu...

Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

The Science of the total environment
Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduce natural disaster risk. Unfortunately, wetlands are declining much faster than forests. The safeguarding of the wetlands also needs knowledge of the ...

The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability.

The Journal of pharmacy and pharmacology
OBJECTIVES: The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (T ) and choice of diffusion cell on model quality and performance.