Environmental Health

Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems.

Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally a...

Machine learning-driven identification of early-life air toxic combinations associated with childhood asthma outcomes.

Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that cause or may cause serious health effects. Although individual air toxics have been associated with asthma, only a limited number of studies have specifically examined combinations of air toxics associated with the disease. We geocoded air toxic levels from the US National Air Toxics Assessment (NATA)...

Signal Quality Assessment of PPG Signals using STFT Time-Frequency Spectra and Deep Learning Approaches.

Photoplethysmography (PPG) is an important signal which contains much physiological information like heart rate and cardiovascular health etc. However...

Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations.

The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) i...

Drivers of harmful algal blooms in coastal areas of Eastern Mediterranean: a machine learning methodological approach.

Harmful algal species are present in the Mediterranean Sea and are often associated with toxic events affecting the nearby coastal zones. The presence...

CyanoPATH: a knowledgebase of genome-scale functional repertoire for toxic cyanobacterial blooms.

CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyanobacteria harmful algal blooms (CyanoHABs) in eutro...

Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto-ML.

Artificial Intelligence (AI) and machine learning (ML) have now spawned a new field within health care and health science research. These new predicti...

Latest Developments in Robotic Percutaneous Coronary Intervention.

Interventional cardiovascular medicine has seen constant progress over the last few decades. Since the first angiograms and percutaneous transluminal ...

Biohybrid soft robots with self-stimulating skeletons.

Bioinspired hybrid soft robots that combine living and synthetic components are an emerging field in the development of advanced actuators and other r...

Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography.

Although heart failure with reduced ejection fraction (HFrEF) is a common clinical syndrome and can be modified by the administration of appropriate m...

Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States.

This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30,...

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning.

Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated ge...

Deep learning for in vivo near-infrared imaging.

Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial a...

[Preparation of brazilein from by high performance countercurrent chromatography].

Brazilein is among the main chemical constituents of . It has diverse pharmacological activities. Modern pharmacological studies have shown that the c...

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model.

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target....

Bio-protective effects of subsp. against aflatoxin b1 genotoxicity on human blood lymphocytes: a native probiotic strain isolated from Iranian camel milk.

BACKGROUND AND PURPOSE: Aflatoxin B1 is one of the main poisonous substances in certain kinds of fungi all over the world. The toxin is a serious heal...

Artificial intelligence and machine learning for protein toxicity prediction using proteomics data.

Instead of only focusing on the targeted drug delivery system, researchers have a great interest in developing peptide-based therapies for the procure...

Estimating Reliability of Signal Quality of Physiological Data from Data Statistics Itself for Real-time Wearables.

Artificial intelligence (AI) algorithms including machine and deep learning relies on proper data for classification and subsequent action. However, r...

Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle.

Genetic control methods of mosquito vectors of malaria, dengue, yellow fever, and Zika are becoming increasingly popular due to the limitations of oth...

Sustainable manufacturing of sensors onto soft systems using self-coagulating conductive Pickering emulsions.

Compliant sensors based on composite materials are necessary components for geometrically complex systems such as wearable devices or soft robots. Com...