Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such

Fulvic acids (FAs) are known to regulate the fate of mercury (Hg) in sediments, but the key effects of their properties are still unclear. In this study, field investigations and simulation experiments were conducted in a heavy metal-polluted wetland to identify FA characteristics and their association with the production and bioaccumulation of methylmercury (MeHg). Compared to permanently inundated

Free Nitrous Acid (FNA) pre-treatment is a promising technology demonstrated effective in improving waste activated sludge degradability and anaerobic digestion (AD) performance. Pre-treatment conditions including FNA concentration and treatment duration determine operational and capital cost of full-scale implementation, which have not been studied in long-term experiments. The knowledge of FNA pre-treatment

Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model for biogas prediction is developed using deep learning (DL). We propose a hybrid DL architecture, i.e., DA–LSTM–VSN, wherein a dual-stage-attention (DA)-based

Souring is the unwanted formation of hydrogen sulfide (H2S) by sulfate-reducing microorganisms (SRM) in sewer systems and seawater flooded oil reservoirs. Nitrate treatment (NT) is one of the major methods to alleviate souring: The mechanism of souring remediation by NT is stimulation of nitrate reducing microorganisms (NRM) that depending on the nitrate reduction pathway can outcompete SRM for common

Advances in high-throughput sequencing technologies and bioinformatics approaches over almost the last three decades have substantially increased our ability to explore microorganisms and their functions – including those that have yet to be cultivated in pure isolation. Genome-resolved metagenomic approaches have enabled linking powerful functional predictions to specific taxonomical groups with increasing

Small, low-income, and rural communities across the United States are disproportionately exposed to arsenic contaminated drinking water because existing treatment solutions are too expensive and difficult to operate. This paper describes efforts to overcome some barriers and limitations of conventional iron electrocoagulation (Fe-EC) to enable its use in the rural Californian (U.S.) context. Barriers

We argue that doctoral education in water needs an elevated focus towards educating game changers who can drive innovation and change towards more sustainable futures across academic and non-academic settings. Today's doctoral graduates in water are increasingly employed outside academia, and challenged to understand complex and interconnected systems, to integrate and synthesize information from different