Environmental Health

Fusion of multi-scale feature extraction and adaptive multi-channel graph neural network for 12-lead ECG classification.

BACKGROUND AND OBJECTIVE: The 12-lead electrocardiography (ECG) is a widely used diagnostic method in clinical practice for cardiovascular diseases. The potential correlation between interlead signals is an important reference for clinical diagnosis but is often overlooked by most deep learning methods. Although graph neural networks can capture the associations between leads through edge topology...

Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning.

Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using real-world air pollutant data from Taipei City, this study integrates diverse factors, including traffic flow, speed, rainfall patterns, and meteorologi...

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin

The diffusion models (DMs) have demonstrated the remarkable capability of generating images via learning the noised score function of data distribut...

Adaptive Detoxification: Safeguarding General Capabilities of LLMs through Toxicity-Aware Knowledge Editing

Large language models (LLMs) exhibit impressive language capabilities but remain vulnerable to malicious prompts and jailbreaking attacks. Existing ...

Learning A Robust RGB-Thermal Detector for Extreme Modality Imbalance

RGB-Thermal (RGB-T) object detection utilizes thermal infrared (TIR) images to complement RGB data, improving robustness in challenging conditions. ...

DeepMBEnzy: An AI-Driven Database of Mycotoxin Biotransformation Enzymes.

Mycotoxins are toxic fungal metabolites that pose significant health risks. Enzyme biotransformation is a promising option for detoxifying mycotoxins ...

Policy Optimized Text-to-Image Pipeline Design

Text-to-image generation has evolved beyond single monolithic models to complex multi-component pipelines. These combine fine-tuned generators, adap...

Personalized Query Auto-Completion for Long and Short-Term Interests with Adaptive Detoxification Generation

Query auto-completion (QAC) plays a crucial role in modern search systems. However, in real-world applications, there are two pressing challenges th...

Diverse Perspectives Illuminate the Intestinal Toxicity of Traditional and Biodegradable Agricultural Film Microplastics to under Varying Exposure Sequences.

The widespread use of plastic agricultural films necessitates a thorough evaluation of environmental risks posed by soil microplastics (MPs). While th...

An Open-Source Python Framework and Synthetic ECG Image Datasets for Digitization, Lead and Lead Name Detection, and Overlapping Signal Segmentation

We introduce an open-source Python framework for generating synthetic ECG image datasets to advance critical deep learning-based tasks in ECG analys...

Benign-to-Toxic Jailbreaking: Inducing Harmful Responses from Harmless Prompts

Optimization-based jailbreaks typically adopt the Toxic-Continuation setting in large vision-language models (LVLMs), following the standard next-to...

Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)

Transformer-based language models, though not explicitly trained to mimic brain recordings, have demonstrated surprising alignment with brain activi...

Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation.

Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks...

Prediction of Drug-Induced Nephrotoxicity Using Chemical Information and Transcriptomics Data.

Prediction of drug-induced nephrotoxicity is an important task in the drug discovery and development pipeline. Chemical information-based machine lear...

Machine learning-based analysis on factors influencing blood heavy metal concentrations in the Korean CHildren's ENvironmental health Study (Ko-CHENS).

Heavy metal concentration in pregnant women affects neurocognitive and behavioral development of their infants and children. The majority of existing ...

Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects

Conventional AI evaluation approaches concentrated within the AI stack exhibit systemic limitations for exploring, navigating and resolving the huma...

Harnessing natural embodied intelligence for spontaneous jellyfish cyborgs.

Jellyfish cyborgs present a promising avenue for soft robotic systems, leveraging the natural energy-efficiency and adaptability of biological systems...

Diagnostic value of small dense low-density lipoprotein and trace elements in coronary artery disease.

Coronary artery disease (CAD) is a worldwide leading cause of death. Considering that 20%-40% of patients with CAD have a long asymptomatic period of ...

Responsible Diffusion Models via Constraining Text Embeddings within Safe Regions

The remarkable ability of diffusion models to generate high-fidelity images has led to their widespread adoption. However, concerns have also arisen...

Integrating machine learning and traditional methods for cadmium prediction and bioavailability assessment in Paeoniae Radix Alba: a case study from Bozhou, Anhui Province.

Soil heavy metal contamination, particularly cadmium (Cd), poses a significant risk to ecosystems and human health. This study investigates the distri...