AI Medical Compendium Journal:
The Science of the total environment

Showing 91 to 100 of 226 articles

Comparative role of charcoal, biochar, hydrochar and modified biochar on bioavailability of heavy metal(loid)s and machine learning regression analysis in alkaline polluted soil.

The Science of the total environment
Pot experiment was performed aimed to assess the comparative role of charcoal, biochar, hydrochar and thiourea-vegetable modified biochar at 1 and 2 % doses, and <1 mm particle size on the bioavailability of Cd, Pb, As, Ni, Cu and Zn, and enhance NPK...

An artificial intelligence-based model for predicting reproductive toxicity of bisphenol analogues mixtures to the rotifer Brachionus calyciflorus.

The Science of the total environment
The joint toxicity effects of mixtures, particularly reproductive toxicity, one of the main causes of aquatic ecosystem degradation, are often overlooked as it is impractical to test all mixtures. This study developed and evaluated the following mode...

Illuminating patterns of firefly abundance using citizen science data and machine learning models.

The Science of the total environment
As insect populations decline in many regions, conservation biologists are increasingly tasked with identifying factors that threaten insect species and developing effective strategies for their conservation. One insect group of global conservation c...

Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferation.

The Science of the total environment
Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanob...

Enhancing biomass conversion to bioenergy with machine learning: Gains and problems.

The Science of the total environment
The growing concerns about environmental sustainability and energy security, such as exhaustion of traditional fossil fuels and global carbon footprint growth have led to an increasing interest in alternative energy sources, especially bioenergy. Rec...

A data-driven approach for revealing the linkages between differences in electrochemical properties of biochar during anaerobic digestion using automated machine learning.

The Science of the total environment
Biochar is commonly used to enhance the anaerobic digestion of organic waste solids and wastewater, due to its electrochemical properties, which intensify the electron transfer of microorganisms attached to its large surface area. However, it is diff...

3D multi-robot olfaction in naturally ventilated indoor environments: Locating a time-varying source at unknown heights.

The Science of the total environment
Source localization is significant for mitigating indoor air pollution and safeguarding the well-being and safety of occupants. While most study focuses on mechanical ventilation and static sources, this study explores the less-explored domain of loc...

Ecotoxicological impacts of landfill sites: Towards risk assessment, mitigation policies and the role of artificial intelligence.

The Science of the total environment
Waste disposal in landfills remains a global concern. Despite technological developments, landfill leachate poses a hazard to ecosystems and human health since it acts as a secondary reservoir for legacy and emerging pollutants. This study provides a...

Digital technologies to unlock safe and sustainable opportunities for medical device and healthcare sectors with a focus on the combined use of digital twin and extended reality applications: A review.

The Science of the total environment
Medical devices have increased in complexity where there is a pressing need to consider design thinking and specialist training for manufacturers, healthcare and sterilization providers, and regulators. Appropriately addressing this consideration wil...

Employing hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake.

The Science of the total environment
Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of Cyan...