Environmental Health

Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor.

The retrieval of hit/lead compounds with novel scaffolds during early drug development is an important but challenging task. Various generative models have been proposed to create drug-like molecules. However, the capacity of these generative models to design wet-lab-validated and target-specific molecules with novel scaffolds has hardly been verified. We herein propose a generative deep learning ...

Dark-Channel Enhanced-Compensation Net: An end-to-end inner-reflection compensation method for immersive projection system.

Immersive projection display system is widely adopted in virtual reality and various exhibition halls. How to maintain high display quality in an immersive projection environment with uneven illumination and the color deviation caused by the inter-reflection of light is still a challenging task. In this paper, we innovatively propose a deep learning-based radiation compensation for an L-shaped pro...

Molecular Networking and On-Tissue Chemical Derivatization for Enhanced Identification and Visualization of Steroid Glycosides by MALDI Mass Spectrometry Imaging.

Spatial metabolomics describes the spatially resolved analysis of interconnected pathways, biochemical reactions, and transport processes of small mol...

Multimodal collective swimming of magnetically articulated modular nanocomposite robots.

Magnetically responsive composites can impart maneuverability to miniaturized robots. However, collective actuation of these composite robots has rare...

Development of an Artificial Neural Network Algorithm Embedded in an On-Site Sensor for Water Level Forecasting.

Extreme weather events cause stream overflow and lead to urban inundation. In this study, a decentralized flood monitoring system is proposed to provi...

Predicting ammonia nitrogen in surface water by a new attention-based deep learning hybrid model.

Ammonia nitrogen (NH-N) is closely related to the occurrence of cyanobacterial blooms and destruction of surface water ecosystems, and thus it is of g...

Measure emissions to manage emissions.

In the 30 years since the world began negotiating the reduction of greenhouse gas (GHG) emissions, no one has identified exactly where all that pollut...

Data-driven predictive modeling of PM concentrations using machine learning and deep learning techniques: a case study of Delhi, India.

The present study intends to use machine learning (ML) and deep learning (DL) models to forecast PM concentration at a location in Delhi. For this pur...

Detection of arrhythmia in 12-lead varied-length ECG using multi-branch signal fusion network.

Automatic detection of arrhythmia based on electrocardiogram (ECG) plays a critical role in early prevention and diagnosis of cardiovascular diseases....

Segmentation of trabecular bone microdamage in Xray microCT images using a two-step deep learning method.

INTRODUCTION: One of the current approaches to improve our understanding of osteoporosis is to study the development of bone microdamage under mechani...

Introduction to the Theme "Development of New Drugs: Moving from the Bench to Bedside and Improved Patient Care".

Investigations in pharmacology and toxicology range from molecular studies to clinical care. Studies in basic and clinical pharmacology and in preclin...

PM2.5 forecasting for an urban area based on deep learning and decomposition method.

Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe ai...

Deep learning for religious and continent-based toxic content detection and classification.

With time, numerous online communication platforms have emerged that allow people to express themselves, increasing the dissemination of toxic languag...

Environmental toxicity risk evaluation of nitroaromatic compounds: Machine learning driven binary/multiple classification and design of safe alternatives.

Nitroaromatic compounds (NACs) represent a significant source of organic pollutants in the environment. In this study, a well-rounded dataset containi...

Air Quality Index prediction using an effective hybrid deep learning model.

Environmentalism has become an intrinsic part of everyday life. One of the greatest challenge to the environment's long-term existence is the air poll...

Identification of micro- and nanoplastics released from medical masks using hyperspectral imaging and deep learning.

Apart from other severe consequences, the COVID-19 pandemic has inflicted a surge in personal protective equipment usage, some of which, such as medic...

DDCNN: A Deep Learning Model for AF Detection From a Single-Lead Short ECG Signal.

With the popularity of the wireless body sensor network, real-time and continuous collection of single-lead electrocardiogram (ECG) data becomes possi...

Ensemble classification combining ResNet and handcrafted features with three-steps training.

This work presents an ECG classifier for variable leads as a contribution to the Computing in Cardiology Challenge/CinC Challenge 2021. It aims to int...

Research on the Predictive Analysis of Park Landscape Design and Cost Based on RNN Model.

As people's awareness of the environment gradually increases and their requirements for the comfort of living space become higher, landscape design ha...

Artificial ecosystem optimization with Deep Learning Enabled Water Quality Prediction and Classification model.

The majority of what is needed to maintain life is found in the approximately 70 percent of the earth's surface that is composed of water. Water quali...