Environmental Health

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos.

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9.

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug-drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed a...

A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines.

The reformations of the electrical power sector have resulted in very dynamic and competitive market that has changed many elements of the power indus...

Application of artificial intelligence based on synchrosqueezed wavelet transform and improved deep extreme learning machine in water quality prediction.

Water quality prediction is the basis for the prevention and control of water pollution. In this paper, to address the problem of low prediction accur...

Real-time image-based air quality estimation by deep learning neural networks.

Air quality profoundly impacts public health and environmental equity. Efficient and inexpensive air quality monitoring instruments could be greatly b...

Assessment of medical waste generation, associated environmental impact, and management issues after the outbreak of COVID-19: A case study of the Hubei Province in China.

COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the e...

Chemical Reactivity Prediction: Current Methods and Different Application Areas.

The ability to predict chemical reactivity of a molecule is highly desirable in drug discovery, both ex vivo (synthetic route planning, formulation, s...

An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection.

The formalization and solution of supplier selection problems (SSPs) based on sustainable (economic, environmental, and social) indicators have become...

Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable en...

Mycobacterium abscessus drug discovery using machine learning.

The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the develope...

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world.

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-1...

Gibberellic acid-induced hepatorenal dysfunction and oxidative stress: Mitigation by quercetin through modulation of antioxidant, anti-inflammatory, and antiapoptotic activities.

The plant growth regulator gibberellic acid (GA3) is widely used in agriculture in many countries. However, little is known about its danger to human ...

Assessment of the effect of sub-lethal acute toxicity of Emamectin benzoate in using multiple biomarker approach.

Emamectin benzoate (EMB) is a potent neurotoxin agent, widely used for ectoparasites control in aquaculture, but their detailed toxicological implicat...

Photocatalytic dye degradation and photoexcited anti-microbial activities of green zinc oxide nanoparticles synthesized extracts.

Drug-resistant superbugs (DRS) were isolated from hospital sewage waste and confirmed by a 16S rDNA molecular technique as , , , and . Green nanotechn...

Deciphering urban traffic impacts on air quality by deep learning and emission inventory.

Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future me...

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach.

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of t...

Application of Deep Learning in Lung Cancer Imaging Diagnosis.

Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mai...

An Ambidextrous STarfish-Inspired Exploration and Reconnaissance Robot (The ASTER-bot).

As more roboticists are turning to Nature for design inspiration, it is becoming increasingly apparent that multisystem-level investigations of biolog...

Structure analysis and non-invasive detection of cadmium-phytochelatin2 complexes in plant by deep learning Raman spectrum.

Plants synthesize phytochelatins to chelate in vivo toxic heavy metal ions and produce nontoxic complexes for tolerating the stress. Detection of the ...

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking.

The size of cities has been continuously increasing because of urbanization. The number of public and private transportation vehicles is rapidly incre...