Environmental Health

Task-based Regularization in Penalized Least-Squares for Binary Signal Detection Tasks in Medical Image Denoising

Image denoising algorithms have been extensively investigated for medical imaging. To perform image denoising, penalized least-squares (PLS) problems can be designed and solved, in which the penalty term encodes prior knowledge of the object being imaged. Sparsity-promoting penalties, such as total variation (TV), have been a popular choice for regularizing image denoising problems. However, suc...

Vision-based autonomous structural damage detection using data-driven methods

This study addresses the urgent need for efficient and accurate damage detection in wind turbine structures, a crucial component of renewable energy infrastructure. Traditional inspection methods, such as manual assessments and non-destructive testing (NDT), are often costly, time-consuming, and prone to human error. To tackle these challenges, this research investigates advanced deep learning a...

Mitigating GenAI-powered Evidence Pollution for Out-of-Context Multimodal Misinformation Detection

While large generative artificial intelligence (GenAI) models have achieved significant success, they also raise growing concerns about online infor...

AirTOWN: A Privacy-Preserving Mobile App for Real-time Pollution-Aware POI Suggestion

This demo paper presents \airtown, a privacy-preserving mobile application that provides real-time, pollution-aware recommendations for points of in...

T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation

Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, ...

CogMorph: Cognitive Morphing Attacks for Text-to-Image Models

The development of text-to-image (T2I) generative models, that enable the creation of high-quality synthetic images from textual prompts, has opened...

Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities

The appearance of surface impurities (e.g., water stains, fingerprints, stickers) is an often-mentioned issue that causes degradation of automated v...

Focus-N-Fix: Region-Aware Fine-Tuning for Text-to-Image Generation

Text-to-image (T2I) generation has made significant advances in recent years, but challenges still remain in the generation of perceptual artifacts,...

Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency

Multimodal Large Language Models (MLLMs) have achieved impressive performance and have been put into practical use in commercial applications, but t...

A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies or the opening or closing...

Can Explainable AI Assess Personalized Health Risks from Indoor Air Pollution?

Acknowledging the effects of outdoor air pollution, the literature inadequately addresses indoor air pollution's impacts. Despite daily health risks...

Rapid Identification of Metal Resistance Genes Using an Enhanced ResNet Deep Learning Model Trained on a largely Expanded BacMet-Based Database

Heavy metal pollution poses significant risks to both the environment and public health. Effective management requires not only reducing contaminants ...

ESPWA: a deep learning-enabled tool for precision-based use of endocrine therapy in resource-limited settings

Cancer morbidity disproportionately affects patients in low- and middle-income countries (LMICs), where timely and accurate tumor profiling is often n...

Deep learning-based image quantification of epithelial cell shapes and its application to polycystic kidney disease

Cell shape is a fundamental determinant of tissue architecture and organ function. In epithelial tissues, cytoskeletal organization and tight junction...

Active learning-guided optimization of cell-free biosensors for lead testing in drinking water

Point-of-use diagnostics based on allosteric transcription factors (aTFs) are promising tools for environmental monitoring and human health. However, ...

Interpretable Machine Learning and Comparative Genomics Reveal Microbial Plastic-Degrading (Microbeyt) Potential

Plastic pollution poses a critical environmental threat, and microbial enzymes represent a sustainable strategy for polymer degradation. We present a ...

A Biosecurity Agent for Lifecycle LLM Biosecurity Alignment

Large language models (LLMs) are increasingly integrated into biomedical re-search workflows-from literature triage and hypothesis generation to exper...

Efficacy and safety evaluation of artificial intelligence-identified antimicrobial peptides for use against avian pathogenic Escherichia coli in the poultry industry

The overuse of antibiotics in both veterinary and human medicine has resulted in the emergence of antibiotic-resistant bacteria, prompting a search fo...

PlasticEnz: An integrated database and screening tool combining homology and machine learning to identify plastic-degrading enzymes in meta-omics datasets

PlasticEnz is a new open-source tool for detecting plastic-degrading enzymes (plastizymes) in metagenomic data by combining sequence homology-based se...

SLOGEN: A Structure-based Lead Optimization Model Unifying Fragment Generation and Screening

Lead optimization plays an important role in preclinical drug discovery. While deep learning has accelerated this process, structure-based approaches ...