Environmental Health

Novel application of neural network modelling for multicomponent herbal medicine optimization.

The conventional method for effective or toxic chemical substance identification of multicomponent herbal medicine is based on single component separation, which is time-consuming, labor intensive, inefficient, and neglects the interaction and integrity among the components; therefore, it is necessary to find an alternative routine to evaluate the components more efficiently and scientifically. In...

Antiproliferative, neurotoxic, genotoxic and mutagenic effects of toxic cyanobacterial extracts.

Cyanobacteria are the rich resource of various secondary metabolites including toxins with broad pharmaceutical significance. The aim of this work was to evaluate the antiproliferative, neurotoxic, genotoxic and mutagenic effects of cyanobacterial extracts containing Microcystin-LR (MCLR) . ELISA analysis results showed that MCLR contents of five cyanobacterial extracts were 2.07 ng/mL, 1.43 ng/mL...

DeltaDelta neural networks for lead optimization of small molecule potency.

The capability to rank different potential drug molecules against a protein target for potency has always been a fundamental challenge in computationa...

Artificial neural network model to predict transport parameters of reactive solutes from basic soil properties.

Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types is time-consuming, laborious, expensive and practi...

A Novel Tendon-Driven Soft Actuator with Self-Pumping Property.

Soft actuators and robotics have been widely researched in recent years mainly due to their compliance to environments and safe interaction with human...

Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance.

In this study, we use a deep convolutional neural network (CNN) to develop a model that predicts ozone concentrations 24 h in advance. We have evaluat...

Monitoring Commercial Ibuprofen Potency Changes Over 1 Year When Stored in a Household Setting.

Most over-the-counter medications are labeled for storage in a dry, room temperature environment. Despite this, many households store medications in ...

A Novel Air Quality Early-Warning System Based on Artificial Intelligence.

The problem of air pollution is a persistent issue for mankind and becoming increasingly serious in recent years, which has drawn worldwide attention....

Deep learning for multi-year ENSO forecasts.

Variations in the El Niño/Southern Oscillation (ENSO) are associated with a wide array of regional climate extremes and ecosystem impacts. Robust, lon...

Deep learning identifies accurate burst locations in water distribution networks.

Pipe bursts in water distribution networks lead to considerable water loss and pose risks of bacteria and pollutant contamination. Pipe burst localisa...

Estimating daily PM concentrations in New York City at the neighborhood-scale: Implications for integrating non-regulatory measurements.

Previous PM related epidemiological studies mainly relied on data from sparse regulatory monitors to assess exposure. The introduction of non-regulato...

Novel small molecule retrograde transport blocker confers post-exposure protection against ricin intoxication.

Ricin is a highly toxic type 2 ribosome-inactivating protein (RIP) which is extracted from the seeds of castor beans. Ricin is considered a potential ...

Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors.

The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candida...

Synthesis of Electrocardiogram V-Lead Signals From Limb-Lead Measurement Using R-Peak Aligned Generative Adversarial Network.

Recently, portable electrocardiogram (ECG) hardware devices have been developed using limb-lead measurements. However, portable ECGs provide insuffici...

Accurate detection of atrial fibrillation from 12-lead ECG using deep neural network.

Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram (ECG) is regarded as the gold standard for AF diagnosis. H...

Multi-Level Comparison of Machine Learning Classifiers and Their Performance Metrics.

Machine learning classification algorithms are widely used for the prediction and classification of the different properties of molecules such as toxi...

Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaig...

Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.

Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but their combined impact on hypercholesterolemia (HC) is ...

A hybrid hierarchical soft computing approach for the technology selection problem in brick industry considering environmental competencies: A case study.

Brick manufacturing is an important industry which produces some fundamental building materials. Since brick production industries have environmental ...

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches.

Textile industry wastewaters, which cause serious problems in the environment and human health, include synthetic dyes, complex organic pollutants, su...