Environmental Health

Toxicovigilance 2.0 - modern approaches for the hazard identification and risk assessment of toxicants in human beings: A review.

The attempt to define toxicovigilance can be based on defining its fundamental principles: prevention of infections with toxic substances, collecting information on poisonings, both in terms of their sources and side effects, and confirming poisonings, with the aim of improving treatment. Substances referred to include both those originating from animal bites, ingested inadvertently, and those res...

Optimization strategy of community planning for environmental health and public health in smart city under multi-objectives.

As population density increases, environmental hygiene and public health become increasingly severe. As the space where residents stay for the longest time and have the most profound impact on their physical and mental health, the quality of the environment in urban communities largely determines the degree to which residents engage in physical activity, bear the risk of pollution exposure, and ob...

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicol...

Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more practical approach to arrhythmia detection. Using...

Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.

With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), whic...

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

The breathtaking economic development put a heavy toll on ecology, especially on water pollution. Efficient water resource management has a long-term ...

Molecular marker identification, antioxidant, antinociceptive, and anti-inflammatory responsiveness of malonic acid capped silver nanoparticle.

Nano-sized silver has drawn a great deal of attention in the field of health sciences owing to its remarkable therapeutic applications. Interestingly,...

A comprehensive review on artificial intelligence in water treatment for optimization. Clean water now and the future.

Given the severe effects that toxic compounds present in wastewater streams have on humans, it is imperative that water and wastewater streams polluti...

A neural network model for the evolution of learning in changing environments.

Learning from past experience is an important adaptation and theoretical models may help to understand its evolution. Many of the existing models stud...

An integrated approach on the enzymatic and antioxidant mechanisms of four commercially available essential oils ( and ) traditionally used topically for their anti-inflammatory effects.

Despite the increasing number of essential oils being reported on their potential therapeutic effects, some remain relatively unknown on their biolog...

Antimicrobial activity of nature-inspired molecules against multidrug-resistant bacteria.

Multidrug-resistant bacterial infections present a serious challenge to global health. In addition to the spread of antibiotic resistance, some bacter...

Natural deep eutectic solvents-based green extraction of vanillin: optimization, purification, and bioactivity assessment.

The sustainable extraction of natural compounds has recently attracted significant attention. The extraction of high-quality natural vanillin in activ...

Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings.

Snake venom contains many toxic proteins that can destroy the circulatory system or nervous system of prey. Studies have found that these snake venom ...

Antifungal activity of eumelanin-inspired indoylenepheyleneethynylene against .

is an opportunistic fungal pathogen that causes meningitis in >152,000 immunocompromised individuals annually, leading to 112,000 yearly deaths. The ...

A denoising method based on deep learning for proton radiograph using energy resolved dose function.

Proton radiograph has been broadly applied in proton radiotherapy which is affected by scattered protons which result in the lower spatial resolution ...

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization.

For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are ...

Mushroom tyrosinase enzyme catalysis: synthesis of larvicidal active geranylacetone derivatives against and molecular docking studies.

The grindstone process, which uses tyrosinase as a catalyst, was used to create analogues of geranylacetone. Tyrosinase was used to prepare the Mannic...

Green synthesis of gold and silver nanoparticles using crude extract of and evaluation of their antibacterial, antioxidant and photocatalytic activities.

Green synthesis of metal nanoparticles (NPs) has received extensive attention over other conventional approaches due to their non-toxic nature and mor...

An integrated approach to occupational health risk assessment of manufacturing nanomaterials using Pythagorean Fuzzy AHP and Fuzzy Inference System.

Nanomaterials (NMs) have the potential to be hazardous owing to their unique physico-chemical properties. Therefore, the need for Health Risk Assessme...

Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild.

The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. ...