Environmental Health

Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputs.

Particulate matter (PM) stands out as a highly perilous form of atmospheric pollution, posing significant risks to human health by triggering or worsening numerous heart, brain, and lung ailments, and even increasing the likelihood of cancer and premature mortality. Therefore, ensuring accurate monitoring of PM levels holds paramount significance, particularly urban zones of dense population. Stil...

Occurrence, Sources, and Prioritization of Per- and Polyfluoroalkyl Substances (PFASs) in Drinking Water from Yangtze River Delta, China: Focusing on Emerging PFASs.

As regulations ban legacy PFASs, many emerging PFASs are being developed, leading to their release into the aquatic environment and drinking water. However, research studies on these emerging PFASs in drinking water are limited, and current standards only cover a few legacy PFASs, leaving many emerging PFASs unregulated and their toxicity unknown. Therefore, a machine learning-based suspect screen...

Unique bioaccumulation and biosynthesis of arsenobetaine in marine fish.

Arsenic (As) contamination represents a significant global concern, particularly prevalent in regions such as China, South Asia, and Southeast Asia. A...

Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.

Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appe...

Process management method in head and neck cancer patient care.

Management of patients with head and neck cancer (HNC) is a complex process that involves extensive knowledge on (at least) the discipline of surgery,...

Immune-related gene risk model establishment and role of key gene FUCA1 in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare type of tumor closely associated with asbestos exposure. Increasing evidence shows that hig...

Unveiling sources of organophosphate esters in marine environments utilizing multi-factor multi-modal high-dimensional clustering algorithm.

In marine environments, the sources of organophosphate esters (OPEs), particularly emerging OPEs (eOPEs) remain primarily unclear and present signific...

Identification of marine microplastics by laser-induced fluorescence spectroscopy: 1-Dimensional convolutional neural network and continuous convolutional model.

Marine microplastic pollution is a serious threat to ecosystems and human health, and its identification is of great significance for determining the ...

Spatial Risks of Microplastics in Soils and the Cascading Effects Thereof.

Microplastic (MP) pollution has become a significant global concern in soil systems. The spatial risk of MPs in soils, the cascading effects of climat...

A new method for drinking water quality risk assessment based on data-driven.

Risk assessment of water quality plays a crucial role in sustainable management of water resource. However, evaluating drinking water quality risk for...

Physics-informed neural networks involving unsteady friction for transient pipe flow.

A robust physics-informed neural network (PINN) approach is developed to accurately predict pressure and flow velocity during the water hammer event, ...

Laboratory quality management system fundamentals.

A laboratory quality management system (LQMS) enables the effective operation of laboratories of all types and sizes. With rapid advances in technolog...

Respiration Drives Dynamic Metal-Organic Framework for Smart Photoresponse to Volatile Toxic Vapors and Their Photodynamic Sterilization.

Using aggregation-induced emission luminous (AIEgens) containing dynamic molecular rotor structures as linkers to construct flexible smart luminescent...

Machine Learning-Based Calibration and Performance Evaluation of Low-Cost Internet of Things Air Quality Sensors.

Low-cost air quality sensors (LCSs) are increasingly being used in environmental monitoring due to their affordability and portability. However, their...

Holistic characterization of water quality parameters to understand the ecological impacts of eutrophication.

The naturally oligotrophic waters of the Florida Keys, U.S.A., can be impacted by small increases in nutrients, which are reflected by increased phyto...

A Transfer Learning-Based VGG-16 Model for COD Detection in UV-Vis Spectroscopy.

Chemical oxygen demand (COD) serves as a key indicator of organic pollution in water bodies, and its rapid and accurate detection is crucial for envir...

Toxic hearts: Machine learning uncovers the cardiovascular toll of heavy metals in the Philippine landscape.

Machine learning-assisted fluorescence/smartphone dual-mode platform for lead ion detection using the novel polyimide covalent organic framework.

Unintended leakage of toxic and lead ion (Pb) ions poses high harmful to human health and environment, hence its monitoring and detection is of utmost...

Exploring indigenous South African plants as alternative treatments for dermatophytosis: Focusing on the antifungal properties and mechanism of action of Searsia lancea.

Numerous medicinal plants are reported to have activity against dermatophytes, however, there are limited studies providing insights into their mechan...

Simultaneous determination of five alkaloids in extracted and non-extracted poppy APIs by HPLC.

BACKGROUND: Poppy Active Pharmaceutical Ingredients (APIs) are mainly used in the production of antitussives, analgesics, and other preparations. The ...