Environmental Health

Non-traditional socio-environmental and geospatial determinants of Alzheimer's disease-related dementia mortality.

IMPORTANCE: Recent data point to the impact of non-traditional environmental and social factors on Alzheimer's Disease-Related Dementias (ADRD) mortality. Our study aimed to determine the extent to which antecedent air pollution, social vulnerability, and geospatial features in the environment associate with ADRD mortality.

Identification and designing an analgesic opioid cyclic peptide from Defensin 4 of Mesobuthus martensii Karsch scorpion venom with more effectiveness than morphine.

Considering the limitations of use and side effects of existing analgesics, the discovery of new analgesics is necessary. Venoms of organisms are an important source of analgesic peptides. In this study, using computational biology methods such as molecular docking simulation, molecular dynamics, and predictions of physicochemical and biological properties based on various machine learning algorit...

Revealing the impacts of the built environment factors on pedestrian-weighted air pollutant concentration using automated and interpretable machine learning.

Urban air pollution poses significant health risks, especially to pedestrians due to their proximity to pollutants and lack of physical protection. Un...

A lightweight spatial and spectral CNN model for classifying floating marine plastic debris using hyperspectral images.

Marine plastic debris poses a significant environmental threat. In order to study and combat this pollution, efficient and automated detection methods...

Evaluating marine environmental pollution using Fuzzy Analytic Hierarchy Process (FAHP): A comprehensive framework for sustainable coastal and oceanic management.

Marine pollution poses a significant threat to ecosystems, biodiversity, and human health, necessitating a structured evaluation framework. This study...

Multi-machine learning methods for rapid and synergistic inversion of groundwater contamination source, hydrogeologic parameter and boundary condition.

The application of machine learning methods to the groundwater pollution inversion problem has become a hot research topic in recent years. However, a...

Spatio-temporal prediction of groundwater vulnerability based on CNN-LSTM model with self-attention mechanism: A case study in Hetao Plain, northern China.

Located in northern China, the Hetao Plain is an important agro-economic zone and population centre. The deterioration of local groundwater quality ha...

Efficient Numerical Integration for Finite Element Trunk Spaces in 2D and 3D using Machine Learning: A new Optimisation Paradigm to Construct Application-Specific Quadrature Rules

Finite element methods usually construct basis functions and quadrature rules for multidimensional domains via tensor products of one-dimensional co...

Double-Diffusion: Diffusion Conditioned Diffusion Probabilistic Model For Air Quality Prediction

Air quality prediction is a challenging forecasting task due to its spatio-temporal complexity and the inherent dynamics as well as uncertainty. Mos...

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment

Positron Emission Tomography / Computed Tomography (PET/CT) plays a critical role in medical imaging, combining functional and anatomical informatio...

Prediction of Specificity of α-Conotoxins to Subtypes of Human Nicotinic Acetylcholine Receptors with Semi-supervised Machine Learning.

Conotoxins are a family of highly toxic neurotoxins composed of cysteine-rich peptides produced by marine cone snails. The most lethal cone snail spec...

PLPTP: A Motif-based Interpretable Deep Learning Framework Based on Protein Language Models for Peptide Toxicity Prediction.

Peptide toxicity prediction holds significant importance in drug development and biotechnology, as accurately identifying toxic peptide sequences is c...

EXGnet: a single-lead explainable-AI guided multiresolution network with train-only quantitative features for trustworthy ECG arrhythmia classification

Background: Deep learning has significantly advanced ECG arrhythmia classification, enabling high accuracy in detecting various cardiac conditions. ...

Environmental Change Detection: Toward a Practical Task of Scene Change Detection

Humans do not memorize everything. Thus, humans recognize scene changes by exploring the past images. However, available past (i.e., reference) imag...

Revisiting Transformers with Insights from Image Filtering

The self-attention mechanism, a cornerstone of Transformer-based state-of-the-art deep learning architectures, is largely heuristic-driven and funda...

Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages

Online toxic language causes real harm, especially in regions with limited moderation tools. In this study, we evaluate how large language models ha...

Hybrid Physical Mechanism and Artificial Intelligence-Based Model for Evaluating Nonpoint Source Pesticide Pollution at a Megacity Scale.

Large-scale nonpoint source (NPS) pesticide pollution is a growing concern in urban areas; however, modeling of such pollution is constrained by chall...

Accurate Identification of MDMB-Type Synthetic Cannabinoids through Design of Dual Excited-State Intramolecular Proton Transfer Site Probe and Deep-Learning.

Synthetic cannabinoids, a novel class of highly toxic psychoactive substances with various disguised forms, have posed significant risks to public saf...

FuXi-Air: Urban Air Quality Forecasting Based on Emission-Meteorology-Pollutant multimodal Machine Learning

Air pollution has emerged as a major public health challenge in megacities. Numerical simulations and single-site machine learning approaches have b...

Heartcare Suite: Multi-dimensional Understanding of ECG with Raw Multi-lead Signal Modeling

We present Heartcare Suite, a multimodal comprehensive framework for finegrained electrocardiogram (ECG) understanding. It comprises three key compo...