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Forecasting beef production and quality using large-scale integrated data from Brazil.

Journal of animal science
With agriculture rapidly becoming a data-driven field, it is imperative to extract useful information from large data collections to optimize the production systems. We compared the efficacy of regression (linear regression or generalized linear regr...

Towards a global understanding of the drivers of marine and terrestrial biodiversity.

PloS one
Understanding the distribution of life's variety has driven naturalists and scientists for centuries, yet this has been constrained both by the available data and the models needed for their analysis. Here we compiled data for over 67,000 marine and ...

Vitamin D deficiency among children aged 10-18 years in Sri Lanka.

The Ceylon medical journal
BACKGROUND: Vitamin D deficiency (VDD) and insufficiency (VDI) are public health problems in many countries, and limited data is available on the prevalence of VDD/VDI in Sri Lanka.

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...

Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches.

BMC infectious diseases
BACKGROUND: Recent reports of the National Ministry of Health and Treatment of Iran (NMHT) show that Gilan has a higher annual incidence rate of leptospirosis than other provinces across the country. Despite several efforts of the government and NMHT...

Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning.

Geospatial health
Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is endemic. A vaccine is not available and has yet to reach the market due to the economic burden of d...

Artificial intelligence reveals environmental constraints on colour diversity in insects.

Nature communications
Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial intelligence-can reveal subtle but robust patterns of colour feature variation along an ecological gr...

Remote Control of Greenhouse Vegetable Production with Artificial Intelligence-Greenhouse Climate, Irrigation, and Crop Production.

Sensors (Basel, Switzerland)
The global population is increasing rapidly, together with the demand for healthy fresh food. The greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI...

Using artificial neural networks to predict future dryland responses to human and climate disturbances.

Scientific reports
Land degradation and sediment remobilisation in dryland environments is considered to be a significant global environmental problem. Given the potential for currently stabilised dune systems to reactivate under climate change and increased anthropoge...

Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Computational and mathematical methods in medicine
Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first point of care in hospitals for urgent and critically ill patients. Therefore, effective management of hospital's ED is crucial in improving the quality...